Software Engineer jobs at Twitter - 711 jobs

A leading social media platform in Palo Alto is looking for a Technical Lead Manager in Ads Conversion Modeling. This role includes leading the User Match Prediction roadmap, developing conversion models, and partnering with various teams to drive performance. Ideal candidates have a strong software engineering background, machine learning knowledge, and 6+ years of relevant experience. The position offers a competitive salary and hybrid work flexibility. #J-18808-Ljbffr

A leading social media platform in Palo Alto is looking for a Technical Lead Manager in Ads Conversion Modeling. This role includes leading the User Match Prediction roadmap, developing conversion models, and partnering with various teams to drive performance. Ideal candidates have a strong software engineering background, machine learning knowledge, and 6+ years of relevant experience. The position offers a competitive salary and hybrid work flexibility. #J-18808-Ljbffr

A global technology company in Mountain View is seeking a Senior Silicon Physical Design Engineer to lead physical design methodologies. This role requires 5+ years of advanced design experience, particularly in SoC cycles and low power designs. The ideal candidate holds a Bachelor's or Master's in Electrical Engineering and is skilled in System Verilog and TCL scripting. You'll drive innovations that power the next generation of hardware across Google's data centers. #J-18808-Ljbffr

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Team Name: Feature Serving LinkedIn is the world's largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Job Description This role can be based in Mountain View, CA, San Francisco, CA, or Bellevue, WA. Join us to push the boundaries of scaling large models together. The team is responsible for scaling LinkedIn's AI model training, feature engineering and serving with hundreds of billions of parameters models and large scale feature engineering infra for all AI use cases from recommendation models, large language models, to computer vision models. We optimize performance across algorithms, AI frameworks, data infra, compute software, and hardware to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, vLLM, Hugginface, DeepSpeed etc.) in the team. Additionally, this team focussed on technologies like LLMs, GNNs, Incremental Learning, Online Learning and Serving performance optimizations across billions of user queries Model Training Infrastructure: As an engineer on the AI Training Infra team, you will play a crucial role in building the next-gen training infrastructure to power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like Huggingface, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like model parallelism, tensor parallelism, Zero++ etc. Finally, you will assist in and guide the development of containerized pipeline orchestration infrastructure, including developing and distributing stable base container images, providing advanced profiling and observability, and updating internally maintained versions of deep learning frameworks and their companion libraries like Tensorflow, PyTorch, DeepSpeed, GNNs, Flash Attention. PyTorch Lightning and more and more. Feature Engineering: this team shapes the future of AI with the state-of-the-art Feature Platform, which empowers AI Users to effortlessly create, compute, store, consume, monitor, and govern features within online, offline, and nearline environments, optimizing the process for model training and serving. As an engineer in the team, you will explore and innovate within the online, offline, and nearline spaces at scale (millions of QPS, multi terabytes of data, etc), developing and refining the infrastructure necessary to transform raw data into valuable feature insights. Utilizing leading open-source technologies like Spark, Beam, and Flink and more, you will play a crucial role in processing and structuring feature data, ensuring its most optimal storage in the Feature Store, and serving feature data with high performance. Model Serving Infrastructure: this team builds low latency high performance applications serving very large & complex models across LLM and Personalization models. As an engineer, you will build compute efficient infra on top of native cloud, enable GPU based inference for a large variety of use cases, cuda level optimizations for high performance, enable on-device and online training. Challenges include scale (10s of thousands of QPS, multiple terabytes of data, billions of model parameters), agility (experiment with hundreds of new ML models per quarter using thousands of features), and enabling GPU inference at scale. ML Ops: The MLOps and Experimentation team is responsible for the infrastructure that runs MLOps and experimentation systems across LinkedIn. From Ramping to Observability, this org powers the AI products that define LinkedIn. This team, inside MLOps, is responsible for AI Metadata, Observability, Orchestration, Ramping and Experimentation for all models; building tools that enable our product and infrastructure engineers to optimize their models and deliver the best performance possible. As a Software Engineer, you will have first-hand opportunities to advance one of the most scalable AI platforms in the world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI industry. Responsibilities Designing, implementing, and optimizing the performance of large-scale distributed serving or training for personalized recommendation as well as large language models. Improving the observability and understandability of various systems with a focus on improving developer productivity and system sustenance. Partner with peers, leads and partners to define, scope, prioritize, and build impactful features at a high velocity. Qualifications Basic Qualifications Bachelor's Degree in Computer Science or related technical discipline, or equivalent practical experience 1+ years of experience in the industry with leading/ building deep learning systems. Experience with Java, C++, Python, Go, Rust, C# and/or Functional languages such as Scala or other relevant coding languages Experience, qualifications in Machine Learning, AI Preferred Qualifications 2+ years of relevant work experience MS or PhD in Computer Science or related technical discipline Experience building ML applications, LLM serving, GPU serving. Experience with search systems or similar large-scale distributed systems Experience with distributed data processing engines like Flink, Beam, Spark etc., feature engineering, Experience in distributed machine learning training infrastructure, including technologies like Horovod, PyTorch FSDP, DeepSpeed, Hugginface, PyTorch Lightning, LLMs, GNNs, MLFlow, Kubeflow and large scale distributed systems Familiarity with containers and container orchestration systems like Kubernetes Experience in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX Suggested Skills ML Algorithm Development Experience in Machine Learning and Deep Learning Distributed Systems You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $114,000 - $189,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Team Name: Feature Serving LinkedIn is the world's largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Job Description This role can be based in Mountain View, CA, San Francisco, CA, or Bellevue, WA. Join us to push the boundaries of scaling large models together. The team is responsible for scaling LinkedIn's AI model training, feature engineering and serving with hundreds of billions of parameters models and large scale feature engineering infra for all AI use cases from recommendation models, large language models, to computer vision models. We optimize performance across algorithms, AI frameworks, data infra, compute software, and hardware to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, vLLM, Hugginface, DeepSpeed etc.) in the team. Additionally, this team focussed on technologies like LLMs, GNNs, Incremental Learning, Online Learning and Serving performance optimizations across billions of user queries Model Training Infrastructure: As an engineer on the AI Training Infra team, you will play a crucial role in building the next-gen training infrastructure to power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like Huggingface, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like model parallelism, tensor parallelism, Zero++ etc. Finally, you will assist in and guide the development of containerized pipeline orchestration infrastructure, including developing and distributing stable base container images, providing advanced profiling and observability, and updating internally maintained versions of deep learning frameworks and their companion libraries like Tensorflow, PyTorch, DeepSpeed, GNNs, Flash Attention. PyTorch Lightning and more and more. Feature Engineering: this team shapes the future of AI with the state-of-the-art Feature Platform, which empowers AI Users to effortlessly create, compute, store, consume, monitor, and govern features within online, offline, and nearline environments, optimizing the process for model training and serving. As an engineer in the team, you will explore and innovate within the online, offline, and nearline spaces at scale (millions of QPS, multi terabytes of data, etc), developing and refining the infrastructure necessary to transform raw data into valuable feature insights. Utilizing leading open-source technologies like Spark, Beam, and Flink and more, you will play a crucial role in processing and structuring feature data, ensuring its most optimal storage in the Feature Store, and serving feature data with high performance. Model Serving Infrastructure: this team builds low latency high performance applications serving very large & complex models across LLM and Personalization models. As an engineer, you will build compute efficient infra on top of native cloud, enable GPU based inference for a large variety of use cases, cuda level optimizations for high performance, enable on-device and online training. Challenges include scale (10s of thousands of QPS, multiple terabytes of data, billions of model parameters), agility (experiment with hundreds of new ML models per quarter using thousands of features), and enabling GPU inference at scale. ML Ops: The MLOps and Experimentation team is responsible for the infrastructure that runs MLOps and experimentation systems across LinkedIn. From Ramping to Observability, this org powers the AI products that define LinkedIn. This team, inside MLOps, is responsible for AI Metadata, Observability, Orchestration, Ramping and Experimentation for all models; building tools that enable our product and infrastructure engineers to optimize their models and deliver the best performance possible. As a Software Engineer, you will have first-hand opportunities to advance one of the most scalable AI platforms in the world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI industry. Responsibilities Designing, implementing, and optimizing the performance of large-scale distributed serving or training for personalized recommendation as well as large language models. Improving the observability and understandability of various systems with a focus on improving developer productivity and system sustenance. Partner with peers, leads and partners to define, scope, prioritize, and build impactful features at a high velocity. Qualifications Basic Qualifications * Bachelor's Degree in Computer Science or related technical discipline, or equivalent practical experience * 1+ years of experience in the industry with leading/ building deep learning systems. * Experience with Java, C++, Python, Go, Rust, C# and/or Functional languages such as Scala or other relevant coding languages * Experience, qualifications in Machine Learning, AI Preferred Qualifications * 2+ years of relevant work experience * MS or PhD in Computer Science or related technical discipline * Experience building ML applications, LLM serving, GPU serving. * Experience with search systems or similar large-scale distributed systems * Experience with distributed data processing engines like Flink, Beam, Spark etc., feature engineering, * Experience in distributed machine learning training infrastructure, including technologies like Horovod, PyTorch FSDP, DeepSpeed, Hugginface, PyTorch Lightning, LLMs, GNNs, MLFlow, Kubeflow and large scale distributed systems * Familiarity with containers and container orchestration systems like Kubernetes * Experience in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX Suggested Skills * ML Algorithm Development * Experience in Machine Learning and Deep Learning * Distributed Systems You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $114,000 - $189,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: * Documents in alternate formats or read aloud to you * Having interviews in an accessible location * Being accompanied by a service dog * Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Job Description This role will be based in Mountain View, CA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. The team builds high-quality products and services to ensure the health and reliability of LinkedIn at scale. Our products empower LinkedIn engineers to deliver value to members at a high velocity and without defects. We strive to prevent these defects early in the SDLC process, automating solutions to mitigate issues on behalf of engineers when possible. In addition, our metrics have high visibility across R&D and are leveraged by the lines of business to drive long-term strategy and investment in their organizations. As a Technical Lead on the Edge and Traffic team, you will drive the technical direction and development of LinkedIn's traffic engineering, content delivery, and load balancing infrastructure. You will play a critical role in shaping the scalability, reliability, and efficiency of our global traffic systems while collaborating closely with engineers across product and infrastructure teams to build the next generation of high-performance networking solutions. Responsibilities Develop and drive technical roadmaps for LinkedIn's content delivery, proxy, traffic routing, and load balancing infrastructure. Establish engineering and design best practices for building high-scale, reliable, and performant traffic systems. Lead design reviews, incident post-mortems, and production readiness reviews, ensuring adherence to reliability and scalability standards. Significantly contribute to the design and development of key projects, providing hands-on engineering leadership. Collaborate closely with workload owners to identify and address both current and emerging technical requirements. Design, deploy, and optimize traffic routing and security over multiple content delivery networks. Implement and maintain proxy systems to enhance traffic distribution, load balancing, and fault tolerance. Drive automation, observability, and fault tolerance initiatives, reducing downtime and improving MTTR (Mean Time to Recovery). Analyze network traffic telemetry to optimize load balancing, manage traffic spikes, and plan for future capacity needs. Establish and monitor key performance metrics, SLAs, and SLOs for DNS and traffic routing systems. Act as a technical mentor, recruiting, developing, and coaching junior engineers to strengthen the team's expertise. Qualifications Basic Qualifications Bachelor's degree in Computer Science, Network Engineering, Electrical Engineering, or equivalent experience 8+ years of experience in network infrastructure, site reliability engineering, or large-scale distributed systems. Expertise in traffic engineering, load balancing, and DNS resolution in high-scale, globally distributed environments. Coding experience in one or more languages such as Python, Go, Java, or C++. Preferred Qualifications MS or PhD degree in Computer Science or related technical discipline 10+ years experience working in cloud-scale or web-scale environments. Deep understanding of edge networks, CDNs, and software-defined networking (SDN). Experience with networking protocols and traffic management technologies (e.g., BGP, Anycast, TLS, HTTP/2, QUIC). Hands-on experience with traffic routing platforms such as IPVS, Apache Traffic Server (ATS), HAProxy, or Envoy. Proven ability to drive architectural decisions, solve complex scaling challenges, and optimize system performance. Excellent communication and collaboration skills, with the ability to influence and align cross-functional teams. Suggest Skills Edge & Network Engineering Load Balancing Distributed Systems Technical Leadership You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $218,000 to $357,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Our mission is to provide a reliable, efficient, and intuitive development ecosystem that empowers iOS engineers to be highly productive. Our team supports hundreds of engineers who build LinkedIn's iOS applications, spanning the entire development lifecycle - from code authoring and code quality to build and test infrastructure. We develop and maintain the core infrastructure, shared components, developer experience tools, and distributed testing systems to meet the challenges of scale that come with a large codebase and engineering team. Our initiatives focus on improving productivity through code modularization, test and code isolation, and robust dependency management. We ensure developers have access to the latest Apple technologies by rapidly integrating new tooling and releases. Additionally, we optimize CI pipelines and workflows for speed and reliability through these efforts. Responsibilities Design and implement user-facing features for LinkedIn's native iOS application, leveraging Apple's mobile frameworks for multi-threading, data persistence, and adaptive UI to support multiple device types. Utilize cutting-edge technologies and libraries recommended by Apple to build responsive, high-performance native iOS apps. Develop scalable mobile applications using LinkedIn's internal libraries and infrastructure. Make architectural decisions by applying synchronous and asynchronous design patterns, writing clean, efficient code, and delivering with speed and quality. Build and maintain robust CI pipelines to support efficient build and test workflows for LinkedIn's iOS applications. Produce high-quality software that is unit tested, peer-reviewed, and continuously integrated. Provide technical leadership by driving best engineering practices and executing large-scale, cross-functional, and mission-critical programs. Identify and champion opportunities to enhance engineering productivity across the organization. Qualifications Basic Qualifications • BA/BS in Computer Science or related technical field or equivalent practical experience. • 1+ years of industry experience • Programming experience in languages such as Java, C/C++, Python, Objective-C, Swift, etc. Preferred Qualifications • 2+ years of relevant work experience. • MS or PhD in Computer Science or related technical discipline. Suggest Skills Objective-C Swift iOS development toolchains such as Xcode You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $102,000 to $167,000 . Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Technology leaders collaborate, maintain balance, commit and achieve results - all while upholding immense pride in their quality of work. Our leaders value their craft and inspire their team to do the same. They balance product and technology strategy to put members first. They are responsible for attracting, retaining, engaging and developing their teams while also leading and inspiring them to achieve the goals of LinkedIn. Engineering leaders are champions of LinkedIn to their coworkers, their networks and the tech community. As a Distinguished Engineer at LinkedIn, you will architect and lead the next generation of AI solutions that power LinkedIn's growth ecosystem - from PYMK to Notifications to Agentic Onboarding - by employing the developing state of the art technologies - from reinforcement learning to generative AI and large models. You will develop strategies to drive user retention throughout the user lifecycle across LinkedIn's consumer ecosystem, helping accelerate LinkedIn's vision as a leader within the Growth team. Responsibilities: Help define business strategy and technical strategy and drive alignment cross functionally. Head cross team/cross functional discussions and drive alignment on product/technology strategy. Help build highly scalable systems and applications to enable the organization to achieve its goals. Actively improve the level of craftsmanship at LinkedIn by developing best practices and defining best strategies. Define the bar for quality and efficiency of software systems while balancing business impact, operational impact and cost benefits of design and architectural choices. Establish a culture that values diverse viewpoints while navigating complex decisions. Qualifications Basic Qualifications: Bachelor's degree in Computer Science or a related field, or equivalent experience 10+ years of relevant work experience Experience leading technical projects with multiple stakeholders Preferred Qualifications: PhD in a relevant field or related discipline (machine learning, statistics, computer science etc.), or equivalent research experience 10+ years experience in building engaging AI-powered consumer products at scale, with at least 5 of those years in a technical leadership position Experience in designing and optimizing recommender systems that create highly personalized experiences for LinkedIn's members and scale to solve complex business problems Experience in leading large scale development projects from concept to multiple releases in production Experience of technical leadership guiding and mentoring engineering and operations talent Experience leading high-impact, cross-company initiatives Dream big. Make big, bold moves to define and build the next generation of products Suggested Skills: Mentorship Technical Leadership Machine Learning You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $248,000 to $406,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Our mission is to provide a reliable, efficient, and intuitive development ecosystem that empowers iOS engineers to be highly productive. Our team supports hundreds of engineers who build LinkedIn's iOS applications, spanning the entire development lifecycle - from code authoring and code quality to build and test infrastructure. We develop and maintain the core infrastructure, shared components, developer experience tools, and distributed testing systems to meet the challenges of scale that come with a large codebase and engineering team. Our initiatives focus on improving productivity through code modularization, test and code isolation, and robust dependency management. We ensure developers have access to the latest Apple technologies by rapidly integrating new tooling and releases. Additionally, we optimize CI pipelines and workflows for speed and reliability through these efforts. Responsibilities + Design and implement user-facing features for LinkedIn's native iOS application, leveraging Apple's mobile frameworks for multi-threading, data persistence, and adaptive UI to support multiple device types. + Utilize cutting-edge technologies and libraries recommended by Apple to build responsive, high-performance native iOS apps. + Develop scalable mobile applications using LinkedIn's internal libraries and infrastructure. + Make architectural decisions by applying synchronous and asynchronous design patterns, writing clean, efficient code, and delivering with speed and quality. + Build and maintain robust CI pipelines to support efficient build and test workflows for LinkedIn's iOS applications. + Produce high-quality software that is unit tested, peer-reviewed, and continuously integrated. + Provide technical leadership by driving best engineering practices and executing large-scale, cross-functional, and mission-critical programs. + Identify and champion opportunities to enhance engineering productivity across the organization. Basic Qualifications - BA/BS in Computer Science or related technical field or equivalent practical experience. - 1+ years of industry experience - Programming experience in languages such as Java, C/C++, Python, Objective-C, Swift, etc. Preferred Qualifications - 2+ years of relevant work experience. - MS or PhD in Computer Science or related technical discipline. Suggest Skills + Objective-C + Swift + iOS development toolchains such as Xcode You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $102,000 to $167,000 . Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** **Equal Opportunity Statement** We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: + Documents in alternate formats or read aloud to you + Having interviews in an accessible location + Being accompanied by a service dog + Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. **San Francisco Fair Chance Ordinance ** Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. **Pay Transparency Policy Statement ** As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** **Global Data Privacy Notice for Job Candidates ** Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Our mission is to provide a reliable, efficient, and intuitive development ecosystem that empowers iOS engineers to be highly productive. Our team supports hundreds of engineers who build LinkedIn's iOS applications, spanning the entire development lifecycle - from code authoring and code quality to build and test infrastructure. We develop and maintain the core infrastructure, shared components, developer experience tools, and distributed testing systems to meet the challenges of scale that come with a large codebase and engineering team. Our initiatives focus on improving productivity through code modularization, test and code isolation, and robust dependency management. We ensure developers have access to the latest Apple technologies by rapidly integrating new tooling and releases. Additionally, we optimize CI pipelines and workflows for speed and reliability through these efforts. Responsibilities * Design and implement user-facing features for LinkedIn's native iOS application, leveraging Apple's mobile frameworks for multi-threading, data persistence, and adaptive UI to support multiple device types. * Utilize cutting-edge technologies and libraries recommended by Apple to build responsive, high-performance native iOS apps. * Develop scalable mobile applications using LinkedIn's internal libraries and infrastructure. * Make architectural decisions by applying synchronous and asynchronous design patterns, writing clean, efficient code, and delivering with speed and quality. * Build and maintain robust CI pipelines to support efficient build and test workflows for LinkedIn's iOS applications. * Produce high-quality software that is unit tested, peer-reviewed, and continuously integrated. * Provide technical leadership by driving best engineering practices and executing large-scale, cross-functional, and mission-critical programs. * Identify and champion opportunities to enhance engineering productivity across the organization. Qualifications Basic Qualifications * BA/BS in Computer Science or related technical field or equivalent practical experience. * 1+ years of industry experience * Programming experience in languages such as Java, C/C++, Python, Objective-C, Swift, etc. Preferred Qualifications * 2+ years of relevant work experience. * MS or PhD in Computer Science or related technical discipline. Suggest Skills * Objective-C * Swift * iOS development toolchains such as Xcode You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $102,000 to $167,000 . Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: * Documents in alternate formats or read aloud to you * Having interviews in an accessible location * Being accompanied by a service dog * Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Job Description At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Join us to push the boundaries of scaling large models together. The team is responsible for scaling LinkedIn's AI model training, feature engineering and serving with hundreds of billions of parameters models and large scale feature engineering infra for all AI use cases from recommendation models, large language models, to computer vision models. We optimize performance across algorithms, AI frameworks, data infra, compute software, and hardware to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, vLLM, Hugginface, DeepSpeed etc.) in the team. Additionally, this team focussed on technologies like LLMs, GNNs, Incremental Learning, Online Learning and Serving performance optimizations across billions of user queries. Model Training Infrastructure: As an engineer on the AI Training Infra team, you will play a crucial role in building the next-gen training infrastructure to power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like Huggingface, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like model parallelism, tensor parallelism, Zero++ etc. Finally, you will assist in and guide the development of containerized pipeline orchestration infrastructure, including developing and distributing stable base container images, providing advanced profiling and observability, and updating internally maintained versions of deep learning frameworks and their companion libraries like Tensorflow, PyTorch, DeepSpeed, GNNs, Flash Attention. PyTorch Lightning and more and more. Model Serving Infrastructure: this team builds low latency high performance applications serving very large & complex models across LLM and Personalization models. As an engineer, you will build compute efficient infra on top of native cloud, enable GPU based inference for a large variety of use cases, cuda level optimizations for high performance, enable on-device and online training. Challenges include scale (10s of thousands of QPS, multiple terabytes of data, billions of model parameters), agility (experiment with hundreds of new ML models per quarter using thousands of features), and enabling GPU inference at scale. As a Sr. Staff Software Engineer, you will have first-hand opportunities to advance one of the most scalable AI platforms in the world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI industry. Responsibilities: Owning the technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems. Designing, implementing, and optimizing the performance of large-scale distributed serving or training for personalized recommendation as well as large language models. Improving the observability and understandability of various systems with a focus on improving developer productivity and system sustenance. Mentoring other engineers, defining our challenging technical culture, and helping to build a fast-growing team. Working closely with the open-source community to participate and influence cutting edge open-source projects (e.g., vLLMs, PyTorch, GNNs, DeepSpeed, Huggingface, etc.). Functioning as the tech-lead for several concurrent key initiatives AI Infrastructure and defining the future of AI Platforms. Qualifications Basic Qualifications: BS/BA in Computer Science or related technical field or equivalent technical experience 5+ years of industry experience in software design, development, and algorithm related solutions 5+ years of experience programming in object-oriented languages such as Python, C++, Java, Go, Rust, Scala 2+ years of experience as an architect, or technical leadership position 5+ years of experience in the industry with leading / building deep learning systems Hands-on experience developing distributed systems or other large-scale systems Preferred Qualifications: MS or PhD in Computer Science or related technical discipline. 10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position 10+ years of experience in an object-oriented programming language such as Python, C++, Java, Go, Rust, Scala 5+ years of experience with large-scale distributed systems and client-server architectures Experience building ML applications, LLM serving, GPU serving. Co-author or maintainer of any open-source projects Expertise in machine learning infrastructure, including technologies like MLFlow, Kubeflow and large scale distributed systems Expertise in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX Suggested Skills: ML Algorithm Development Machine Learning and Deep Learning Information retrieval / recommendation systems Technical leadership LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 to $326,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Job Description At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Join us to push the boundaries of scaling large models together. The team is responsible for scaling LinkedIn's AI model training, feature engineering and serving with hundreds of billions of parameters models and large scale feature engineering infra for all AI use cases from recommendation models, large language models, to computer vision models. We optimize performance across algorithms, AI frameworks, data infra, compute software, and hardware to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, vLLM, Hugginface, DeepSpeed etc.) in the team. Additionally, this team focussed on technologies like LLMs, GNNs, Incremental Learning, Online Learning and Serving performance optimizations across billions of user queries. Model Training Infrastructure: As an engineer on the AI Training Infra team, you will play a crucial role in building the next-gen training infrastructure to power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like Huggingface, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like model parallelism, tensor parallelism, Zero++ etc. Finally, you will assist in and guide the development of containerized pipeline orchestration infrastructure, including developing and distributing stable base container images, providing advanced profiling and observability, and updating internally maintained versions of deep learning frameworks and their companion libraries like Tensorflow, PyTorch, DeepSpeed, GNNs, Flash Attention. PyTorch Lightning and more and more. Model Serving Infrastructure: this team builds low latency high performance applications serving very large & complex models across LLM and Personalization models. As an engineer, you will build compute efficient infra on top of native cloud, enable GPU based inference for a large variety of use cases, cuda level optimizations for high performance, enable on-device and online training. Challenges include scale (10s of thousands of QPS, multiple terabytes of data, billions of model parameters), agility (experiment with hundreds of new ML models per quarter using thousands of features), and enabling GPU inference at scale. As a Sr. Staff Software Engineer, you will have first-hand opportunities to advance one of the most scalable AI platforms in the world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI industry. Responsibilities: Owning the technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems. Designing, implementing, and optimizing the performance of large-scale distributed serving or training for personalized recommendation as well as large language models. Improving the observability and understandability of various systems with a focus on improving developer productivity and system sustenance. Mentoring other engineers, defining our challenging technical culture, and helping to build a fast-growing team. Working closely with the open-source community to participate and influence cutting edge open-source projects (e.g., vLLMs, PyTorch, GNNs, DeepSpeed, Huggingface, etc.). Functioning as the tech-lead for several concurrent key initiatives AI Infrastructure and defining the future of AI Platforms. Qualifications Basic Qualifications: BS/BA in Computer Science or related technical field or equivalent technical experience 5+ years of industry experience in software design, development, and algorithm related solutions 5+ years of experience programming in object-oriented languages such as Python, C++, Java, Go, Rust, Scala 2+ years of experience as an architect, or technical leadership position 5+ years of experience in the industry with leading / building deep learning systems Hands-on experience developing distributed systems or other large-scale systems Preferred Qualifications: MS or PhD in Computer Science or related technical discipline. 10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position 10+ years of experience in an object-oriented programming language such as Python, C++, Java, Go, Rust, Scala 5+ years of experience with large-scale distributed systems and client-server architectures Experience building ML applications, LLM serving, GPU serving. Co-author or maintainer of any open-source projects Expertise in machine learning infrastructure, including technologies like MLFlow, Kubeflow and large scale distributed systems Expertise in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX Suggested Skills: ML Algorithm Development Machine Learning and Deep Learning Information retrieval / recommendation systems Technical leadership LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 to $326,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description This role will be based in Mountain View, CA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. As a Sr. Staff Software Engineer of the Compute Infrastructure team at LinkedIn, you will play a crucial role in our ongoing efforts to re-architect our compute infrastructure stack. This is a high-profile, high-impact project that will touch every aspect of our engineering organization. We are looking for experienced professionals who have a proven track record of designing large-scale compute infrastructure and driving consensus. In this role, you will design and implement solutions that enable LinkedIn to scale its compute infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with a team of experienced engineers, including distinguished engineers and technical fellows, to develop and operate solutions that are robust, scalable, and efficient. You will also need to work collaboratively with cross-functional teams and be comfortable operating in a fast-paced, dynamic environment. If you are passionate about building the underlying technology that powers one of the world's most-used internet applications, and have the skills and experience to help us take our compute infrastructure to the next level, we want to hear from you. Apply now to join our team and help shape the future of LinkedIn. Responsibilities -You will directly contribute to LinkedIn's Compute infrastructure strategy. -You will build and operate a platform that allocates hardware resources with necessary physical/logical distribution for fault tolerance and easy maintenance. -You will build and operate world class high performance scheduling/deployment solutions including some of the world's largest Kubernetes clusters to place stateless/stateful services, ML workloads and short running jobs efficiently. -You will help up-level and coach a large team of talented developers. Qualifications Basic Qualifications -5+ years of industry experience in software design, development, and algorithm related solutions -5+ years of experience programming in object-oriented languages such as Java, Go, C/C++, Rust, Rust, Python -Hands-on experience developing large-scale distributed systems -2+ years of experience as an architect, or technical leadership position -BS/BA in Computer Science or related technical field or equivalent technical experience Preferred Qualifications -10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position -10+ years of programming experience in an object-oriented programming language such as Go, Java, C/C++, Rust -5+ years of experience building large-scale compute infrastructure, and distributed systems -Demonstrated understanding of operating system fundamentals, container technologies, and systems knowledge. -Experienced in leading technical teams and mentoring other engineers -Experience building and operating cluster management solutions such as Kubernetes. -Experience with IaaS systems and capacity management. -Experience with networking and security principles. -Deep understanding of Kubernetes architecture and key components (API server, scheduler, kubelet, etc.), with a proven track record of deploying, managing, and troubleshooting Kubernetes clusters. -Strong proficiency in Golang, as it is the primary language. -Solid understanding of networking concepts relevant to Kubernetes, including CNI plugins and pod networking. -Knowledge of Kubernetes security best practices such as RBAC, network policies, and Pod security policies. -Proficiency with monitoring and logging tools such as Prometheus, Grafana, and Fluentd. Suggested Skills -Distributed Systems -Kubernetes -Technical Leadership LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 to $326,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description This role will be based in Mountain View, CA, or Bellevue, WA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. As part of our world-class software engineering team, you will take the lead in building the next-generation infrastructure and platforms for LinkedIn, including but not limited to: service delivery platform, scalable data storage infrastructure, graph infrastructure, analytics platform, streams processing and data pipelines, cutting-edge search platform, best-in-class AI/ML infrastructure, Kubernetes compute infrastructure, media infrastructure, etc. You will work and learn among the best, putting to use your passion for distributed technologies and algorithms, API design and systems design, and your passion for writing code that performs at massive scale. LinkedIn has pioneered many well-known open-source infrastructure projects including Apache Kafka, Pinot, Azkaban, Samza, Venice, Datahub, Feather, etc. We also work with industry standard open source infrastructure technologies like Kubernetes, GRPC and GraphQL - come join our infrastructure teams and share the knowledge with a broader community while making a real impact within our company. As a Sr. Staff Software Engineer, you will be a key technical leader and role model within the organization. We are looking for a technical lead who designs and develops technology to serve business and technology objectives, aligns points of view across teams and makes trade offs to help achieve the goals of individual teams as well as LinkedIn's broader goals. You will foster LinkedIn's culture and values around transformation, collaboration and results. You will work closely with technical leadership and management within and outside our organization to contribute to building best-in-class core systems infrastructure for LinkedIn. Responsibilities: Deliver impact by driving innovation while building and shipping software at scale Provide architectural guidance and mentorship to up-level the engineering organization Actively improve the level of craftsmanship at LinkedIn by developing best practices and defining best strategies Design products/services/tools and code that can be used by others while upholding operational impact of all decisions Functioning as the tech-lead for multiple key initiatives, identify problems and opportunities and lead teams to architect, design, implement and operationalize systems Partner closely with teams within the org and customers to execute on the vision for long-term success of our core infrastructure teams Working closely with the open-source community to participate and influence cutting edge open-source projects. Keep a platform first approach while designing products/service Qualifications Basic Qualifications: BS/BA in Computer Science or related technical field or equivalent technical experience 5+ years of industry experience in software design, development, and algorithm related solutions 5+ years of experience programming in object-oriented languages such as C/C++, Java, Go, Rust, Python, Scala 2+ years of experience as an architect, or technical leadership position Hands-on experience developing large-scale, distributed systems, and databases Preferred Qualifications: MS or PhD degree in Computer Science or related technical discipline 10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position 10+ years of experience in an object-oriented programming language such as C/C++, Java, Go, Rust, Python, Scala 5+ years of experience with large-scale distributed systems and client-server architectures Experience in architecting and designing large-scale distributed systems related to data infrastructure, IaaS, ML/AI infrastructure, storage, graph, Kubernetes, and platforms. Suggested Skills: Distributed Systems Technical Leadership Infrastructure as a Service (IaaS) Systems Infrastructure LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 to $326,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description This role will be based in Mountain View, CA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. As a Sr. Staff Software Engineer of the Compute Infrastructure team at LinkedIn, you will play a crucial role in our ongoing efforts to re-architect our compute infrastructure stack. This is a high-profile, high-impact project that will touch every aspect of our engineering organization. We are looking for experienced professionals who have a proven track record of designing large-scale compute infrastructure and driving consensus. In this role, you will design and implement solutions that enable LinkedIn to scale its compute infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with a team of experienced engineers, including distinguished engineers and technical fellows, to develop and operate solutions that are robust, scalable, and efficient. You will also need to work collaboratively with cross-functional teams and be comfortable operating in a fast-paced, dynamic environment. If you are passionate about building the underlying technology that powers one of the world's most-used internet applications, and have the skills and experience to help us take our compute infrastructure to the next level, we want to hear from you. Apply now to join our team and help shape the future of LinkedIn. Responsibilities You will directly contribute to LinkedIn's Compute infrastructure strategy. You will build and operate a platform that allocates hardware resources with necessary physical/logical distribution for fault tolerance and easy maintenance. You will build and operate world class high performance scheduling/deployment solutions including some of the world's largest Kubernetes clusters to place stateless/stateful services, ML workloads and short running jobs efficiently. You will help up-level and coach a large team of talented developers. Qualifications Qualifications Basic Qualifications 5+ years of industry experience in software design, development, and algorithm related solutions 5+ years of experience programming in object-oriented languages such as Java, Go, C/C++, Rust, Rust, Python Hands-on experience developing large-scale distributed systems 2+ years of experience as an architect, or technical leadership position BS/BA in Computer Science or related technical field or equivalent technical experience Preferred Qualifications 10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position 10+ years of programming experience in an object-oriented programming language such as Go, Java, C/C++, Rust 5+ years of experience building large-scale compute infrastructure, and distributed systems Demonstrated understanding of operating system fundamentals, container technologies, and systems knowledge. Experienced in leading technical teams and mentoring other engineers Experience building and operating cluster management solutions such as Kubernetes. Experience with IaaS systems and capacity management. Experience with networking and security principles. Deep understanding of Kubernetes architecture and key components (API server, scheduler, kubelet, etc.), with a proven track record of deploying, managing, and troubleshooting Kubernetes clusters. Strong proficiency in Golang, as it is the primary language. Solid understanding of networking concepts relevant to Kubernetes, including CNI plugins and pod networking. Knowledge of Kubernetes security best practices such as RBAC, network policies, and Pod security policies. Proficiency with monitoring and logging tools such as Prometheus, Grafana, and Fluentd. Suggested Skills Distributed Systems Kubernetes Technical Leadership LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 to $326,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. This role can be based in Mountain View, CA, San Francisco, CA, or Bellevue, WA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Job Description As a staff member of the Compute Infrastructure team at LinkedIn, you will be charged with building the next-generation infrastructure and platforms for LinkedIn. This is a unique opportunity to work on a high-profile, high-impact ongoing project that will touch every aspect of our engineering organization. Specifically, the LinkedIn Kubernetes Infrastructure team provides an on-premises Kubernetes platform for the entire company. The team provides capability to efficiently create Kubernetes clusters on-demand, build multi-clusters solutions, automate upgrades, and intelligently detect and remediate cluster health, etc. In this role, you will be responsible for designing and implementing solutions that will enable LinkedIn to scale its Compute Infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with a team of engineers to develop and operate solutions that are robust, scalable, and efficient. You will also need to work collaboratively with cross-functional teams and be comfortable operating in a fast-paced, dynamic environment. Responsibilities You will own the technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems. You will design, implement, and optimize the performance of large-scale distributed systems with security and compliance in mind. You will Improve the observability and understandability of various systems with a focus on improving developer productivity and system sustenance You will communicate with the team, partners and stakeholders. You will mentor other engineers, define our challenging technical culture, and help to build a fast-growing team You will deliver incremental impact by driving innovation while iteratively building and shipping software at scale You will diagnose technical problems, debug in production environments, and automate routine tasks Qualifications Basic Qualifications BA/BS Degree in Computer Science or related technical discipline, or related practical experience. 4+ years of industry experience in software design, development, and algorithm related solutions. 4+ years experience programming in object-oriented languages such as Java, C++, Python, Go, Rust, C# and/or Functional languages such as Scala or other relevant coding languages Hands on experience developing distributed systems, large-scale systems, databases and/or Backend APIs Preferred Qualifications BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience Experience in architecting, building, and running large-scale distributed systems Experience with Kubernetes (or similar) Ecosystem Experience with Kubernetes controller development, automating cluster management Golang coding experience Experience with industry, open source, and/or academic research in technologies such as Hadoop, Spark, Kubernetes, Feather, GraphQL, GRPC, Apache Kafka, Pinot, Samza or Venice Experience with open-source project management and governance Suggested Skills Distributed Systems Golang Technical Leadership You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170,000 to $277,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Job Description This role can be based in Mountain View, CA, San Francisco, CA, or Bellevue, WA. Join us to push the boundaries of scaling large models together. The team is responsible for scaling LinkedIn's AI model training, feature engineering and serving with hundreds of billions of parameters models and large scale feature engineering infra for all AI use cases from recommendation models, large language models, to computer vision models. We optimize performance across algorithms, AI frameworks, data infra, compute software, and hardware to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, vLLM, Hugginface, DeepSpeed etc.) in the team. Additionally, this team focussed on technologies like LLMs, GNNs, Incremental Learning, Online Learning and Serving performance optimizations across billions of user queries. Model Training Infrastructure: As an engineer on the AI Training Infra team, you will play a crucial role in building the next-gen training infrastructure to power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like Huggingface, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like model parallelism, tensor parallelism, Zero++ etc. Finally, you will assist in and guide the development of containerized pipeline orchestration infrastructure, including developing and distributing stable base container images, providing advanced profiling and observability, and updating internally maintained versions of deep learning frameworks and their companion libraries like Tensorflow, PyTorch, DeepSpeed, GNNs, Flash Attention. PyTorch Lightning and more. Feature Engineering: this team shapes the future of AI with the state-of-the-art Feature Platform, which empowers AI Users to effortlessly create, compute, store, consume, monitor, and govern features within online, offline, and nearline environments, optimizing the process for model training and serving. As an engineer in the team, you will explore and innovate within the online, offline, and nearline spaces at scale (millions of QPS, multi terabytes of data, etc), developing and refining the infrastructure necessary to transform raw data into valuable feature insights. Utilizing leading open-source technologies like Spark, Beam, and Flink and more, you will play a crucial role in processing and structuring feature data, ensuring its most optimal storage in the Feature Store, and serving feature data with high performance. Model Serving Infrastructure: this team builds low latency high performance applications serving very large & complex models across LLM and Personalization models. As an engineer, you will build compute efficient infra on top of native cloud, enable GPU based inference for a large variety of use cases, cuda level optimizations for high performance, enable on-device and online training. Challenges include scale (10s of thousands of QPS, multiple terabytes of data, billions of model parameters), agility (experiment with hundreds of new ML models per quarter using thousands of features), and enabling GPU inference at scale. ML Ops: The MLOps and Experimentation team is responsible for the infrastructure that runs MLOps and experimentation systems across LinkedIn. From Ramping to Observability, this org powers the AI products that define LinkedIn. This team, inside MLOps, is responsible for AI Metadata, Observability, Orchestration, Ramping and Experimentation for all models; building tools that enable our product and infrastructure engineers to optimize their models and deliver the best performance possible. As a Staff Software Engineer, you will have first-hand opportunities to advance one of the most scalable AI platforms in the world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI industry. Responsibilities Owning the technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems. Designing, implementing, and optimizing the performance of large-scale distributed serving or training for personalized recommendation as well as large language models. Improving the observability and understandability of various systems with a focus on improving developer productivity and system sustenance. Mentoring other engineers, defining our challenging technical culture, and helping to build a fast-growing team. Working closely with the open-source community to participate and influence cutting edge open-source projects (e.g., vLLMs, PyTorch, GNNs, DeepSpeed, Huggingface, etc.). Functioning as the tech-lead for several concurrent key initiatives AI Infrastructure and defining the future of AI Platforms. Qualifications Basic Qualifications Bachelor's Degree in Computer Science or related technical discipline, or equivalent practical experience 4+ years of experience in the industry with leading/ building deep learning systems. 4+ years of experience with Java, C++, Python, Go, Rust, C# and/or Functional languages such as Scala or other relevant coding languages Hands-on experience developing distributed systems or other large-scale systems. Preferred Qualifications BS and 8+ years of relevant work experience MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience Previous experience working with geographically distributed co-workers. Outstanding interpersonal communication skills (including listening, speaking, and writing) and ability to work well in a diverse, team-focused environment with other SRE/SWE Engineers, Project Managers, etc. Experience building ML applications, LLM serving, GPU serving. Experience with search systems or similar large-scale distributed systems Expertise in machine learning infrastructure, including technologies like MLFlow, Kubeflow and large scale distributed systems Experience with distributed data processing engines like Flink, Beam, Spark etc., feature engineering, Co-author or maintainer of any open-source projects Familiarity with containers and container orchestration systems Expertise in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX Suggested Skills ML Algorithm Development Machine Learning and Deep Learning Information retrieval / recommendation systems / distributed serving / Big Data is a plus. Communication Stakeholder Management You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170,000 - $277,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For additional information, visit: ************************************** Additional Information Team Name: DragonKnight (Pytorch & LLM Training) Team Team Description: We build LLM training and post-training frameworks to support scalable and efficient LLM model training and optimizations. We also optimize LLM training by developing customized and efficient Triton kernels to improve training throughput and cut memory footprint. Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: Documents in alternate formats or read aloud to you Having interviews in an accessible location Being accompanied by a service dog Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ********************************************

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed. Join us to transform the way the world works. Job Description At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This role will be hybrid in LinkedIn's Sunnyvale, CA campus. Securing and protecting data is core to building trust with our members and for LinkedIn's success. Within Information Security at LinkedIn, the mission of the Key Management and Cryptography team is to secure and protect our members' data by developing core security services to support management of encryption keys and application secrets. By building developer-friendly cryptographic libraries and APIs, we enable engineering teams across the company to create secure features to protect our members' data. Trust is a key building block in LinkedIn's commitment to putting our members first, and we are an important part of that commitment. As a staff software engineer, you will be responsible for leading and executing on complex projects, and designing and developing scalable services and developer-friendly libraries to empower LinkedIn to defend against the misuse of data. We are looking for an engineer with sound technical acumen, and the ability to lead and grow other engineers on the team. You will own your space and have the unique opportunity to influence the long-term vision and technology roadmap for KMS and Cryptography at LinkedIn. Responsibilities: • You will provide technical leadership, driving and performing best engineering practices to initiate, plan, and execute large-scale, cross functional, and company-wide critical programs. • You will scale distributed applications, make architectural trade-offs applying synchronous and asynchronous design patterns, write code, and deliver with speediness and quality. • You will develop multi-tier scalable, high-volume performing, and reliable user-centric applications that operate 24x7. • You will produce high quality software that is unit tested, code reviewed, and checked in regularly for continuous integration. • Identify, leverage, and successfully evangelize opportunities to improve engineering productivity. • You will participate in key technical and design discussions with technical leads in the team. • You will collaborate with other teams and partners to define and execute on projects. Qualifications Basic Qualifications: • BA/BS Degree in Computer Science or related technical discipline, or related practical experience. • 4+ years experience in software design, development, and algorithm related solutions. • 4+ years programming experience in object-oriented programming languages such as Python, Java, Javascript, C/C++, C#, Objective-C, or Ruby. Preferred Qualifications: • BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience. • Prior experience with Security and/or Cryptography strongly preferred. • Experience in designing and building infrastructure and web services at large scale. • Expert knowledge of computer science, with strong competencies in data structures, algorithms, and software design. Suggested Skills: • Distributed systems • Backend Systems Infrastructure • Kubernetes Infrastructure • Key Management & Cryptography • Technical Leadership You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $152,000 - $248,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For additional information, visit: ************************************** Additional Information Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. 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Please note: This job posting is not for immediate hire but rather an opportunity to submit an application for future consideration. Twitter promotes and protects the public conversation. Twitter is the town square of the internet. At Twitter, we work with one goal in mind: to improve Twitter for our customers, partners, and the people who use it across the world. Brand safety is only possible when human safety is the top priority - This mindset is what drives us forward. Job Description Responsibilities: Lead complex and diverse work, projects, and programs that positively impact multiple teams; Plan and deliver projects that provide significant impact to multiple teams/services; Set your own goals and priorities, making adjustments as necessary for the best results; Provide solutions as a partner within your function. Qualifications Basic Qualifications: 7+ years of relevant experience in software engineering; Strong background in computer science fundamentals, such as data structures and algorithms; Experience in building and operating distributed systems; Strong design and architecture skills; Model of software engineering best practices, including agile development, unit testing, code reviews, design documentation, debugging, and troubleshooting; We believe that leadership comes from everywhere, and it's important that our Senior Developers have the skills to lead complex projects successfully within a large scale organization; Prior experience working with teams across engineering and product management to build features that affect millions of users daily. Preferred Qualifications: Prior leadership experience as technical lead/architect; Proactive external code contributor on public forms. Additional Information We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any other status or characteristic protected by, state, or local laws. San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Twitter provides reasonable accommodations during the recruitment and hiring process upon request. Information received relating to accommodations will be addressed confidentially. To request an accommodation, please contact [email protected] . All your information will be kept confidential according to EEO guidelines.