Operations engineer jobs in Mountain View, CA - 11,882 jobs

A leading semiconductor company in San Jose seeks a Senior Engineer in Product Engineering to manage new product introductions and production support. Candidates should have a Master's degree in Electrical Engineering and two years of relevant experience. Responsibilities include interfacing with manufacturing, conducting failure analyses, and implementing process improvements. This role offers competitive pay and benefits, including healthcare coverage and a performance-based bonus. #J-18808-Ljbffr

Machine Learning Researcher / ML-Ops Engineer About Rivet Rivet is an American company building integrated task systems - fusing hardened hardware with software, sensors, AI, and networking - for industrial workforces and defense personnel. We create capabilities that multiply the effectiveness of every individual and withstand the world's toughest environments. We serve the people who build, operate, maintain, and defend our way of life. From technicians and engineers to first responders and service members, they embody the hard work, ingenuity, and meritocratic values that drive Western prosperity. Yet too often they are forced to rely on outdated tools that fail under modern pressures. Rivet exists to reset that priority. At Rivet, you'll join a mission-driven team that fuses disciplines to deliver decisive outcomes where they matter most. Whether shaping our technology, strengthening our partnerships, or building our culture, every role here contributes to equipping the front lines with the modern systems they deserve. Who Thrives Here People with a deep disdain for bureaucracy, empire building, groupthink, dogma, corporate babble, and wasted time Teammates who want to work exclusively alongside others at the top of their field Experienced, no-nonsense professionals who are execution-focused and deliver high-quality solutions above all else Role Description We are seeking a talented ML Research Engineer to advance our computer vision and sensor fusion capabilities. This role combines cutting‑edge research with practical implementation of machine learning pipelines for imaging, pose estimation, and model optimization. The ideal candidate will have strong expertise in Python, deep learning frameworks, and experience deploying ML models in production environments. You'll explore new ideas, validate them against the state of the art and deliver working prototypes that influence our product and research direction. Role Objectives Implement POCs in Python/C++ to validate ML ideas on embedded hardware Conduct research in imaging and video processing pipelines for AR/VR applications Document learnings and define clear pathways from prototype to production Research and implement model optimization techniques for edge deployment Stay current with latest developments in computer vision and machine learning literature Prototype novel algorithms and validate performance through experimentation Design and implement end-to-end machine learning pipelines using PyTorch and TensorFlow Lite Optimize models for real-time performance on mobile and embedded platforms Implement MLOps best practices for model versioning, monitoring, and continuous integration Create scalable data preprocessing and augmentation pipelines Role Requirements BS with 5+ years of academic or industry experience in machine learning research or applied ML engineering with shipped or published work (or MS with 2+ yrs of the above) Proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow) Experience with ML pipeline development, model deployment, and production monitoring Knowledge of quantization, pruning, and edge deployment techniques Imaging/Video Pipeline: Experience with computational photography, video processing, or camera systems Sensor Fusion & Pose Estimation: Research background in multi-sensor data fusion, tracking, or SLAM Model Optimization: Experience optimizing ML models for mobile/embedded deployment Foundational Knowledge (preferred understanding) Camera Systems: Intrinsic/extrinsic calibration, pinhole model, distortion correction, FOV, color science, exposure control, stereo matching Image Processing: Demosaic, denoising, sharpening, color correction, tone mapping, gamma correction, HDR, super resolution, segmentation, white balance Computer Vision: Feature detection/matching, optical flow, structure from motion, 3D reconstruction, SLAM algorithms IMU & Sensor Fusion: 6DOF/3DOF tracking, gyroscope/accelerometer/magnetometer integration, sensor calibration, sensor fusion algorithms Preferred Qualifications PhD in Computer Vision, Machine Learning, or related field Publications in top-tier conferences (CVPR, ICCV, ECCV, NeurIPS, ICML) Experience with AR/VR or mobile computer vision applications Knowledge of CUDA programming and GPU optimization Experience with cloud platforms (AWS, GCP, Azure) for ML workloads Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines Experience with distributed training and large-scale data processing #J-18808-Ljbffr

Physical Design Engineer - New College Grad 2026 page is loaded## Physical Design Engineer - New College Grad 2026locations: US, CA, Santa Claratime type: Full timeposted on: Posted Todayjob requisition id: JR2009983We are now looking for a Physical Design Engineer!NVIDIA has continuously pioneered and reinvented itself over two decades through various avenues of computing: Graphics, High Performance Computing, Artificial Intelligence, Research, and more. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to tackle, that only we can solve, and that matter to the world. This is our life's work, to amplify human creativity, intelligence, and technology. Today, visual computing is becoming increasingly central to how people interact with technology, and there has never been a more exciting time to join our team. We are looking for a Physical Design Engineer who will be responsible for all aspects of physical design and implementation of Graphics processors, integrated chipsets, and other ASICs targeted at the desktop, laptop, workstation, set-top box and home networking markets.**What you will be doing:*** As a member of the team, you will participate in the efforts in establishing CAD and physical design methodologies (flow and tools development) as well as implementation.* Your day to day will include developing chip floor plan, power/clock distribution, chip assembly and P&R, timing closure, power and noise analysis and back-end verification across multiple projects.* This position requires you to work with EDA vendor (Synopsys, Cadence, Mentor, etc.) tool suites such as: ICC2,PrimeTime, dc\_shell, Innovus, SeaHawk.* You will interact with a diverse team engineers.**What we need to see:*** Completing an BSEE, MSEE or PhD (or equivalent experience).* Deep understanding of VLSI and Physical Design related basics & concepts.* Possess a deep understanding of static timing analysis, clock/power distribution and analysis, RC extraction and correlation, place and route, circuit design and analysis.* Experience in scripting and programming using several of the following languages/tools: Perl, C, C++, TCL, Scheme, Skill, or Make.* Previous internship or project experience in physical design implementation With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a passion for technology, we want to hear from you!Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 96,000 USD - 161,000 USD for Level 1, and 108,000 USD - 184,000 USD for Level 2.You will also be eligible for equity and .Applications for this job will be accepted at least until December 19, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. #J-18808-Ljbffr

A leading technology company in San Jose is seeking an experienced engineer to join their analog/mixed signal IP design team. This role involves designing next generation I/O interfaces, with a strong emphasis on mixed signal design and leading technical projects. The ideal candidate will possess a degree in Electrical Engineering and have hands-on experience with high speed designs and communication tools. This position offers competitive benefits and is not eligible for visa sponsorship. #J-18808-Ljbffr

Meet the Team Join the engineering team building the intelligent backbone of Splunk Observability Cloud. We are committed to leveraging the latest advancements in data science and machine learning to unlock unprecedented value from massive volumes of telemetry-metrics, traces, and logs-at petabyte scale. This role involves researching, developing, and deploying core analytical components focused on streaming anomaly detection, predictive intelligence, and automated root‑cause analysis. If you thrive on the challenge of building enterprise‑grade, scalable ML systems and applying sophisticated techniques to complex, high‑impact problems, you will be instrumental in delivering the full‑stack, real‑time answers and automation required for our customers to achieve true digital resilience across any cloud‑native or hybrid environment. Your Impact Apply the latest Generative AI and Agentic AI to enable AI features in Splunk Observability Collaborate across engineering and product teams to establish robust frameworks for evaluating AI systems' trustworthiness and resilience. Provide technical leadership and mentorship within the team, establishing leading practices for development, testing, and artifact management. Minimum Qualifications Master's degree in computer science or related field and 7+ years of software engineering experience, or bachelor's degree with 10+ years of experience. Experience designing and building scalable cloud‑based systems (AWS, Azure, or GCP), including container orchestration (e.g., Kubernetes, Docker). Proven experience in technical leadership, architecture design, and end‑to‑end feature ownership in AI/ML or platform domains. Experience with API design and frameworks (e.g. OpenAPI, GraphQL, gRPC, REST, etc.) Prior working experience in delivering RAG and Agentic products into production Expert at using vibe coding tools (Claude Code, Codex, Copilot, Windsurf, Cursor) is a must Up To Date knowledge on the latest Agentic and Generative AI industry trend and framework Preferred Qualifications Exceptional problem‑solving skills, with the ability to analyze complex requirements and propose effective solutions. Experience developing, deploying, and maintaining applications in AWS environment with cloud native solutions. Experience monitoring and analyzing metrics, trace, span, and log content Background in observability, generative AI, or model robustness Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. Message to applicants applying to work in the U.S. and/or Canada The starting salary range posted for this position is $183,800.00 to $263,600.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits. Individual pay is determined by the candidate's hiring location, market conditions, job‑related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process. U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long‑term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time. U.S. employees are eligible for paid time away as described below, subject to Cisco's policies: 10 paid holidays per full calendar year, plus 1 floating holiday for non‑exempt employees 1 paid day off for employee's birthday, paid year‑end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco Non‑exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full‑time employees Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations) 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next Additional paid time away may be requested to deal with critical or emergency issues for family members Optional 10 paid days per full calendar year to volunteer For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies. Employees on sales plans earn performance‑based incentive pay on top of their base salary, which is split between quota and non‑quota components, subject to the applicable Cisco plan. For quota‑based incentive pay, Cisco typically pays as follows: .75% of incentive target for each 1% of revenue attainment up to 50% of quota; 1.5% of incentive target for each 1% of attainment between 50% and 75%; 1% of incentive target for each 1% of attainment between 75% and 100%; and Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation. For non‑quota‑based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid. The applicable full salary ranges for this position, by specific state, are listed below: New York City Metro Area: $183,800.00 - $303,100.00 Non‑Metro New York state & Washington state: $163,600.00 - $269,800.00 For quota‑based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined. ** Employees in Illinois, whether exempt or non‑exempt, will participate in a unique time off program to meet local requirements. Cisco is an affirmative action and Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis. Cisco will consider for employment, on a case by case basis, qualified applicants with arrest and conviction records. #J-18808-Ljbffr

Machine Learning Engineer, Level 5 page is loaded## Machine Learning Engineer, Level 5locations: Palo Alto, California: New York - 229 W 43rd St: Bellevue - 110 110th Ave NE: Seattle - 2025 1st Avenue: San Francisco - 1160 Battery Sttime type: Full timeposted on: Posted Todaytime left to apply: End Date: March 31, 2026 (30+ days left to apply)job requisition id: Q126SWEML5is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company's three core products are , a visual messaging app that enhances your relationships with friends, family, and the world; , an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, .teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.We're looking for a Machine Learning Engineer to join Snap Inc!What you'll do:* Build and deploy machine learning models that power core products, serving millions of Snapchatters* Apply modern ML techniques to solve large-scale, real-world problems* Own the full ML lifecycle from data analysis to production deployment* Partner with cross-functional teams to prototype and launch ML-driven features Knowledge, Skills & Abilities:* Strong understanding of machine learning approaches and algorithms* Able to prioritize duties and work well on your own* Ability to work with both internal and external partners* Skilled at solving open ambiguous problems* Strong collaboration and mentorship skills Minimum Qualifications:* Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience* 5+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience* Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning Preferred Qualifications:* Advanced degree in computer science or related field* Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks* Experience working with machine learning, ranking infrastructures, and system design If you have a disability or special need that requires accommodation, please don't be shy and provide us some ."Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success!CompensationIn the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position.These pay zones may be modified in the future.:The base salary range for this position is $209,000-$313,000 annually.:The base salary range for this position is $199,000-$297,000 annually.:The base salary range for this position is $178,000-$266,000 annually.This position is eligible for equity in the form of RSUs. #J-18808-Ljbffr

Tensor is an agentic AI company dedicated to building agentic products that empower individual consumers. Our flagship product, the Tensor Robocar, is the world's first personal Robocar and the first AI agentic vehicle - fully autonomous, automotive-grade, and built for private ownership at scale. Founded in 2016 in Silicon Valley, Tensor is headquartered in San Jose, California, with offices in Barcelona, Singapore, and Dubai. At Tensor, we champion personal AI autonomy and ownership. Our vision is to build a future where everyone owns their own Artificial General Intelligence - a personal AGI that enables more time, freedom, and autonomy. We're forging an alternative path where AGI serves only you, and is controlled solely by you. We provide a competitive compensation package, opportunities for professional growth, participation in a discretionary equity incentive plan, and access to a comprehensive company benefits program, subject to eligibility requirements. Join us to shape the future! Work with brilliant minds on technology transforming automotive industry and make a lasting impact. Locations San Jose, California, US (Salary Range: $75k-$300k USD) Barcelona, Catalonia, Spain Dubai, UAE Responsibilities Research, design and implement novel computer vision and deep learning methods on autonomous driving lidar/camera data Solve difficult problems independently and creatively Communicate effectively with team members and stakeholders Qualifications MS/Ph.D. degree in Computer Science/Robotics/Mechanical Engineering/ Electrical Engineering, or related technical field(or equivalent experience) Strong curiosity about tackling and solving new real-world problems Strong background in Computer Vision and Machine Learning Solid programming skills with c++ and python/torch Experience with points cloud deep learning project is a big plus We appreciate your interest in joining Tensor. Tensor is an equal employment opportunity employer, dedicated to fostering a respectful, supportive, and inclusive workplace for all. We do not discriminate against, and strictly prohibit harassment of, any applicant or employee on the basis of race, color, sex, sexual orientation, gender identity or expression, religion, national origin, age, disability, military or veteran status, genetic information, or any other characteristic protected by applicable law. Tensor also considers qualified applicants with criminal histories in accordance with applicable laws. We are committed to providing equal opportunities for qualified individuals with disabilities. Tensor is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Designed in California. Available around the world. #J-18808-Ljbffr

Palo Alto, CA - Engineering - Hybrid - Full-time Building hardware is like writing software with no debugger, no logs, and only three compile attempts - before mass production. This lack of visibility leads to costly waste and slow iteration. Instrumental's AI-powered platform changes that current reality. We give hardware teams real-time data and insights to catch and fix issues early-so they can build better products, faster, and with less waste. Leading brands like Meta, Bose, and Cisco use Instrumental to accelerate product development and improve yield at scale. We're a ~70-person, mission-driven team that values inclusivity, creativity, and impact. If that resonates with you, we'd love to chat! About The Role: We're looking for a Machine Learning Engineer who's passionate about turning cutting‑edge research into customer impact. You'll help build and scale Instrumental's end‑to‑end ML systems - from prototyping to production - enabling our customers to identify and solve manufacturing issues faster than ever. At Instrumental, ML engineers don't just train models - they own the problem. You'll have full lifecycle ownership: partnering with product and data teams to define features, exploring state‑of‑the‑art methods, curating datasets, iterating rapidly, deploying at scale, and monitoring real‑world performance. Your work will directly shape the product experience for some of the world's most innovative hardware companies. If you want meaningful ownership, tangible impact, and a collaborative environment that values learning and execution - this is the place. What You'll Do: Design, build, and own ML pipelines end‑to‑end-from experimentation to deployment and impact measurement. Collaborate across R&D to deliver holistic solutions that combine ML, software, and user experience. Rapidly prototype algorithms and prioritize work based on real customer needs. Scale production ML systems using modern frameworks and best practices. Lead efforts to acquire, manage, and refine high‑quality datasets for supervised and unsupervised learning. What You'll Need To Be Successful: Experience in writing production code with a focus on maintainability and performance. Experience training deep learning models, including expertise in model selection, training, optimization, and deployment. You have startup DNA: a growth mindset, a bias toward action, and a drive to take ownership of challenging projects with minimal guidance. You're resourceful - when you hit a wall, you find a way around it, learn what you need, and keep moving forward. Computer vision expertise (or a strong foundation in deep learning from other domains, such as NLP). If you don't have direct computer vision experience, a willingness to apply your deep learning knowledge to this area is important. Nice to have: Experience with cloud infrastructure, such as AWS, GCP, or Azure, and familiarity with scaling machine learning models in a cloud‑based environment. We're a growing team that works collaboratively, is supportive of each other, and is highly energized by the opportunity for a large impact. We actively work to promote an inclusive environment, valuing passion and the ability to learn. You're encouraged to apply even if your experience doesn't precisely match the job description! We're additionally open to multiple levels - if you're a Senior, Staff, or Principal‑level engineer, we'd also love to hear from you! Salary range: $168,000 - $270,000 Instrumental is proud to offer a highly‑rated variety of benefits, including health, vision, dental, commuter plans, and parental leave. #J-18808-Ljbffr

About Arc Institute The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: Funding: Arc will fully fund Core Investigators' (PIs') research groups, liberating scientists from the typical constraints of project-based external grants. Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators. Support: Arc aims to provide first-class support-operationally, financially and scientifically-that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction. Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to nearly 200 people. With $650M+ in committed funding and a state‑of‑the‑art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the position We are searching for an experienced and collaborative machine learning research engineer focused on advancing the frontiers of biological foundation models. This role will contribute to the development and application of Arc's frontier DNA foundation model (Evo), Arc's Virtual Cell Initiative focused on developing cell biological models capable of predicting the impact of perturbations and stimuli, and other projects in the context of Institute‑wide machine‑learning efforts. About you You are an innovative machine learning engineer with a deep understanding of ML principles, enabling you to design, modify, and critically evaluate model architectures, not just apply existing ones. You have significant experience in training large deep learning models. You enjoy thinking from first principles, seeking to deeply understand the data and its underlying dynamics to drive effective and innovative modeling strategies. You are excited about working closely with a multidisciplinary team of computational and experimental biologists at Arc to achieve breakthrough capabilities in biological prediction and design tasks. You are a strong communicator, capable of translating complex technical concepts to researchers outside of your domain. You are a continuous learner and are enthusiastic about developing and evaluating a model that impacts many biological disciplines. In this position, you will Actively participate in the design, implementation, and refinement of state‑of‑the‑art foundation models developed in collaboration with other ML researchers and scientists at Arc with the goal of understanding and designing complex biological systems. Engineer large‑scale distributed model pretraining and pipelines for efficient model inference. Enable robust systematic evaluation of trained models. Stay up‑to‑date with the latest advancements in technologies for large‑scale sequence modeling and alignment, and implement the most promising strategies to ensure the underlying models remain state‑of‑the‑art. Work with experimental biologists to ensure that the developed models are grounded in biologically meaningful problems and evaluations. Publish findings through journal publications, white papers, and presentations (both internal to Arc and external). Foster internal and external collaborations centered on generative design of biological systems at Arc Institute. Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others. Job Requirements B.S., M.S. or Ph.D. in Computer Science, Machine Learning or a related field. Minimum of 5‑8+ years of relevant experience in machine‑learning research or ML engineering in an academic (e.g., Ph.D.) or industry research lab. Well‑versed in machine‑learning frameworks such as PyTorch or JAX. Experience with developing distributed training tools such as FSDP, DeepSpeed, or Megatron‑LM. Excellent communication skills, both written and verbal, with a strong track record of presentations and publications. Ability to communicate and collaborate successfully with biologists and software/infrastructure engineers. Motivated to work in a fast‑paced, ambitious, multi‑disciplinary, and highly collaborative research environment. The base salary range for this position is $168,000‑$242,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors. #J-18808-Ljbffr

Remote: This role is based remotely but if you live within a 50-mile radius of Mountain View, you are expected to report to that location three times a week, at minimum. The Role: We are seeking an experienced, technically oriented, impact-driven expert in ML Training Infrastructure with a strong ability to execute hands-on technical work. In this role, you will be responsible for designing and building scalable, reliable, and high-performance AI/ML platform infrastructure to support advanced AI research and model development initiatives. As a Staff ML System Engineer, you will collaborate closely with machine learning engineers, research scientists, and other partners to develop state-of-the-art AI solutions that enable the future of intelligent driving technologies across General Motors vehicles. What You'll Do: Lead the design and development of scalable, reliable, high-performance ML frameworks to support model training at scale. Lead model training performance analysis and optimization solutions to scale distributed training workflows, maximize resource utilization across heterogeneous hardware environments, and reduce costs. Enhance system observability, debuggability, operational excellence, and user experience. Collaborate with cross-functional teams to integrate new features and technologies into the platform. #J-18808-Ljbffr

Physical Design Engineer Job at Apple, Cupertino, CAJob Description Physical Design Engineer Department: Hardware Imagine what you can do here. Apple is a place where extraordinary people gather to do their best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do. Description Apple Inc. has the following available in Cupertino, California, and various unanticipated locations throughout the USA. Responsible for physical design and implementation of partitions. Build partition architecture and drive physical aspects early in the design cycle. Physically implement design partitions (from netlist to tape-out) for a highly complex System-on-Chip (SoC) utilizing state-of-the-art process technology. Work on partition-level place and route (P&R) implementation, including floor planning, clock and power distribution, timing closure, physical and electrical verification. Complete netlist to GDSII implementation for partitions meeting schedule and design goals. Oversee timing, physical, and electrical verification, and drive the signoff closure for the partitions. Resolve design and flow issues related to physical design, identify potential solutions, and drive execution. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $151,091 - $214,500/year, depending on skills, qualifications, experience, and location. PAY & BENEFITS: Apple employees have the opportunity to participate in Apple's stock programs, receive benefits including medical and dental coverage, retirement benefits, discounts, free services, educational reimbursement, and potential bonuses or relocation assistance. Learn more about Apple Benefits. Minimum Qualifications Master's degree or foreign equivalent in Electrical Engineering or related field. 2 years of relevant experience. 1 year of experience with each of the following: Encounter Design System tool, QRC, Calibre, Voltus, Primetime. Preferred Qualifications N/A Apple is an equal opportunity employer committed to inclusion and diversity. We promote equal opportunity for all applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics. Note: Apple benefits, compensation, and employee stock programs are subject to eligibility and other terms. This job posting appears to be active and does not indicate it is expired. #J-18808-Ljbffr

At Protegrity, we lead innovation by using AI and quantum-resistant cryptography to transform data protection across cloud-native, hybrid, on-premises, and open source environments. We leverage advanced cryptographic methods such as tokenization, format-preserving encryption, and quantum-resilient techniques to protect sensitive data. As a global leader in data security, our mission is to ensure that data isn't just valuable but also usable, trusted, and safe. Protegrity offers the opportunity to work at the intersection of innovation and collaboration, with the ability to make a meaningful impact on the industry while working alongside some of the brightest minds. Together, we are redefining how the world safeguards data, enabling organizations to thrive in a GenAI era where data is the ultimate currency. If you're ready to shape the future of data security, Protegrity is the place for you. Protegrity is looking for a Machine Learning Engineer (PhD or MS Required) Location: Menlo Park, CA (In-office, Mon-Thu) The global data privacy software market is projected to grow from $2.36 billion in 2022 to $25.85 billion by 2029. Join us on this journey and make an impact with one of the top 25 global software providers. We look forward to making our world become a better place with you on our team. About the Role This role is designed for a PhD or MS graduate in Computer Science with 2+ years of GenAI experience or equivalent technical projects. You'll work on securing AI workflows and building agentic tools in a collaborative, fast-paced environment. Responsibilities Develop and test GenAI architectures using agentic coding IDEs. Conduct experiments and summarize findings. Present research and experimental results to the team. Fine-tune LLMs and embedding models. Apply ML algorithms to large datasets. Process structured and unstructured data. Participate in architectural design and roadmap discussions. Qualifications PhD or MS in Computer Science. 2+ years GenAI experience or equivalent projects. 3-5 years Python experience. Experience with PyTorch, TensorFlow. Solid understanding of ML algorithms and metrics. Exposure to data security practices. Strong collaboration and learning mindset. Why Choose Protegrity Become a member of a leading Data Protection, Privacy and Security company during one of the best market opportunities to come along in a generation. Competitive Compensation/Total Reward Packages that include: Health Benefits (Health/Dental/Vision) Paid Time Off (PTO) 401K Annual Bonus Incentives Short and Long Term Disability Work on global projects with diverse, energetic, team members who respect each other and celebrate differences Talent First Workforce Should you accept this position, you will be required to consent to and successfully complete a background investigation. This may include, subject to local laws, verification of extended education and additional criminal and civil checks. We offer a competitive salary and comprehensive benefits with generous vacation and holiday time off. All employees are also provided access to ongoing learning & development. Ensuring a diverse and inclusive workplace is our priority. We are committed to an environment of acceptance where you are free to bring your full self to work. All qualified applicants and current employees will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability or veteran status. Please reference Section 12: Supplemental Notice for Job Applicants in our Privacy Policy to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Protegrity USA, Inc., or its parent company, subsidiaries or affiliates, and the purposes for which we use such personal information. #J-18808-Ljbffr

A tech company specializing in AI is seeking a Machine Learning Engineer to enhance its platform by developing and deploying generative AI models. You will collaborate with cross-functional teams to integrate technologies, manage AI models focusing on natural language processing, and work in a fast-paced environment. A Bachelor's degree in Computer Science and expertise in Python and machine learning techniques is required. #J-18808-Ljbffr

UCR (Under Control Robotics) builds multipurpose robots to support human workers in the world's toughest jobs-turning dangerous work from a necessity into a choice. Our work demands reliability, robustness, and readiness for the unexpected-on time, every time. We're assembling a mission-driven team focused on delivering real impact in heavy industry, from construction and mining to energy. If you're driven to build rugged, reliable products that solve real-world problems, we'd love to talk. Position Overview At UCR, building is a team sport. As a machine learning engineer, you'll take ownership and lead the development of advanced machine learning and AI systems powering multipurpose humanoid robots in the real world. You'll design, implement, and optimize learning algorithms that enable robots to move fluidly across diverse environments while performing complex manipulation tasks. Responsibilities Create and optimize learning pipelines for training locomotion policies that generalize across environments Develop and implement machine learning models for robot perception, decision-making, and motion planning Create and optimize computer vision systems for environmental awareness and object recognition Collaborate with the hardware team to integrate learning systems with the physical platforms Design simulation environments for training and testing learning algorithms Collect, process, and analyze field data to improve learning systems continuously Develop metrics and benchmarks to evaluate robot learning performance Stay current with the latest research and innovations in robotics and machine learning Requirements Master's or PhD in Robotics, Computer Science, Machine Learning, or related field 3+ years of experience developing machine learning applications for robotics systems Strong programming skills in Python, C++, and relevant ML frameworks (TensorFlow, PyTorch) Experience with reinforcement learning, computer vision, and motion planning algorithms Familiarity with ROS (Robot Operating System) or similar robotics frameworks Knowledge of control systems and robot kinematics Strong mathematical background in linear algebra, calculus, and statistics Experience with simulation tools for robotics (Gazebo, MuJoCo, Isaac Sim, etc.) Proven track record of implementing ML solutions in robotics applications Experience with legged robot locomotion and dynamic stability control Nice to Have Experience with humanoid robots or complex multi-joint robotic systems Knowledge of model predictive control (MPC) for locomotion Familiarity with trajectory optimization for legged robots Knowledge of industrial environments (construction, energy, mining, or manufacturing) Understanding of safety considerations for learning-based robotic systems Experience with edge computing and deploying ML models on embedded systems Familiarity with human-robot interaction paradigms Background in imitation learning or learning from demonstration Experience with SLAM (Simultaneous Localization and Mapping) techniques To apply, submit your resume here or email ************** . To increase your chances of being selected for an interview, we encourage you to include up to TWO examples of your most representative work featuring hardware demonstrations. #J-18808-Ljbffr

UCR (Under Control Robotics) builds multipurpose robots to support human workers in the world's toughest jobs-turning dangerous work from a necessity into a choice. Our work demands reliability, robustness, and readiness for the unexpected-on time, every time. We're assembling a mission-driven team focused on delivering real impact in heavy industry, from construction and mining to energy. If you're driven to build rugged, reliable products that solve real-world problems, we'd love to talk. Position Overview At UCR, building is a team sport. As a machine learning engineer, you'll take ownership and lead the development of advanced machine learning and AI systems powering multipurpose humanoid robots in the real world. You'll design, implement, and optimize learning algorithms that enable robots to move fluidly across diverse environments while performing complex manipulation tasks. Responsibilities Create and optimize learning pipelines for training locomotion policies that generalize across environments Develop and implement machine learning models for robot perception, decision-making, and motion planning Create and optimize computer vision systems for environmental awareness and object recognition Collaborate with the hardware team to integrate learning systems with the physical platforms Design simulation environments for training and testing learning algorithms Collect, process, and analyze field data to improve learning systems continuously Develop metrics and benchmarks to evaluate robot learning performance Stay current with the latest research and innovations in robotics and machine learning Requirements Master's or PhD in Robotics, Computer Science, Machine Learning, or related field 3+ years of experience developing machine learning applications for robotics systems Strong programming skills in Python, C++, and relevant ML frameworks (TensorFlow, PyTorch) Experience with reinforcement learning, computer vision, and motion planning algorithms Familiarity with ROS (Robot Operating System) or similar robotics frameworks Knowledge of control systems and robot kinematics Strong mathematical background in linear algebra, calculus, and statistics Experience with simulation tools for robotics (Gazebo, MuJoCo, Isaac Sim, etc.) Proven track record of implementing ML solutions in robotics applications Experience with legged robot locomotion and dynamic stability control Nice to Have Experience with humanoid robots or complex multi-joint robotic systems Knowledge of model predictive control (MPC) for locomotion Familiarity with trajectory optimization for legged robots Knowledge of industrial environments (construction, energy, mining, or manufacturing) Understanding of safety considerations for learning-based robotic systems Experience with edge computing and deploying ML models on embedded systems Familiarity with human-robot interaction paradigms Background in imitation learning or learning from demonstration Experience with SLAM (Simultaneous Localization and Mapping) techniques To apply, submit your resume here or email ************** . To increase your chances of being selected for an interview, we encourage you to include up to TWO examples of your most representative work featuring hardware demonstrations. #J-18808-Ljbffr

About the Institute of Foundation Models We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. As part of our team, you'll have the opportunity to work on the core of cutting‑edge foundation model training, alongside world‑class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem‑solving skills will be instrumental in establishing MBZUAI as a global hub for high‑performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers. The Role The Distributed ML Engineer will play a role at the forefront of optimizing performance for the machine learning software stacks, especially at training and inference, and support the team to develop new and cutting‑edge systems. The ideal candidate will have a strong background in parallel computing, and hands‑on experience in system level coding, debug methodologies, and large‑scale machine learning experience. Key Responsibilities Understand, analyze, profile, optimize, and provide guidance to the team on deep learning workloads on state‑of‑the‑art hardware and software platforms to improve their efficiency with different levels of optimization Design and implement performance benchmarks and testing methodologies to evaluate application performance Build tools to automate workload analysis, workload optimization, and other critical workflows Triage system issues and identify bottleneck and inefficiencies by analyzing the sources of issues and the impact on hardware, network and propose solutions to enhance GPU utilization Support the team to develop appropriate kernels and systems for new model architectures and algorithms Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. Represent MBZUAI at industry conferences and events, showcasing the institution's cutting‑edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation. Perform all other duties as reasonably directed by the line manager that are commensurate with the functional objectives. Academic Qualifications Ph.D. in CS, EE or CSEE with 1+ years working experience, OR Masters in CS, EE or CSEE or equivalent experience with 2+ years working experience $150,000 - $450,000 a year Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include Comprehensive medical, dental, and vision benefits Bonus 401K Plan Generous paid time off, sick leave and holidays Paid Parental Leave Employee Assistance Program Life insurance and disability #J-18808-Ljbffr

Gauss Labs is looking for a passionate and talented AI Engineer for developing cutting-edge Industrial AI solutions that will normalize the standard of AI for manufacturing. We are working with the world's best manufacturing customers while accessing the vast amount of real data from their manufacturing processes. We apply state-of-the-art AI technologies to the data and develop unprecedented AI/ML solutions to transform manufacturing to the next level. As an AI Engineer, you will be responsible for translating cutting-edge AI and machine learning research into robust, scalable software solutions. Your work will ensure the seamless integration of models into production environments and contribute to the broader success of AI initiatives across the company. You will develop AI software by working with seasoned Applied Scientists, Software Engineers, and Program Managers located in Palo Alto, California, USA and Seoul, South Korea. Responsibilities Collaborate with AI Scientists to understand model requirements and design scalable, efficient ML pipelines. Build and maintain reliable, performant infrastructure for data processing, model training, evaluation, and deployment. Own the end-to-end implementation of ML systems from research prototypes to production-grade code. Optimize model training/inference, latency, and resource usage to meet performance and system constraints. Develop monitoring, observability, and CI/CD tooling to support the full ML lifecycle in staging and production environments. Ensure engineering best practices in code quality, testing, documentation, and software reliability. Interface with product and engineering teams to understand requirements and drive integration of AI systems into user-facing applications. Key Qualifications BS in Computer Science, Electrical Engineering, Machine Learning, or related technical field. Proficiency in one or more modern programming languages such as Python, C++, or Java with an understanding of algorithms and data structures. Strong expertise in Python data science stack (NumPy, Pandas) and ML/DL frameworks (scikit-learn, PyTorch, TensorFlow) for end-to-end model development. 3+ years building production-ready ML infrastructure, including data pipelines, training/inference workflows, and deployment automation. Solid understanding of software engineering best practices: version control (Git), unit testing, code review, and CI/CD. Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). Experience developing software applications and services with an understanding of design for scalability, performance, and reliability. Strong problem-solving skills, attention to detail, and a collaborative mindset when working with research and product teams. Preferred Qualifications MS or Ph.D. in Computer Science, Electrical Engineering, Machine Learning or related technical field. Knowledge of professional software engineering practices including source control management, code reviews, testing, and continuous integration/deployment. Experience in optimizing training and inferencing structures for large scale ML/DL models. Experience deploying machine learning models into production environments (e.g., batch, real-time, or edge deployments). Experience in distributed/parallel systems, information retrieval, networking, and systems software development. Development experience in a cloud service environment such as Amazon AWS, MS Azure, or Google Cloud Platform. #J-18808-Ljbffr

About Voltai Voltai is developing world models, and agents to learn, evaluate, plan, experiment, and interact with the physical world. We are starting out with understanding and building hardware; electronics systems and semiconductors where AI can design and create beyond human cognitive limits. About the Team Backed by Silicon Valley's top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents. What we're Looking For Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics programs. Proven track record of delivering AI/ML projects from concept to production. Hands‑on experience fine‑tuning and deploying large language models (LLMs) in production environments. Prior experience working with multi‑modal models (e.g., combining text, image, or audio inputs). Bonus Points Background in competitive programming. Contributions to open‑source initiatives. Notable awards or publications in leading journals/conferences. Experience thriving in a fast‑paced, hyper‑growth startup environment. #J-18808-Ljbffr

Member of Technical Staff, Machine Learning Engineer What You'll Work On At Reinforce Labs, we partner directly with customers to build AI systems that enhance the safety and reliability of their complex, high-impact applications. In this role, you'll engage directly with clients to deeply understand their specific challenges, conduct thorough data analysis, and deliver trust and safety AI solutions. You'll implement advanced machine learning techniques including LLMs, reinforcement learning, and deep learning - often translating cutting‑edge research papers into practical applications. This position combines technical depth with significant client‑facing responsibilities. You'll tackle high‑stakes problems with unclear solutions but real‑world consequences. Key responsibilities include: Conducting technical research with customers to map critical workflows and developing sophisticated AI probes that identify potential edge‑case failures Performing comprehensive data analysis to build specialized classifiers that detect subtle risks, violations, and anomalies Implementing and fine‑tuning generative models that can simulate rare or high‑risk scenarios Designing systems that enhance human decision‑making under pressure Our success is measured by real‑world impact. You'll develop and ship solutions that protect people and platforms at scale while building trusted relationships with the clients who depend on our technology. Must‑Have Experience with ML and deep learning frameworks such as PyTorch or TensorFlow Ability to translate cutting‑edge research papers into practical AI applications Hands‑on experience training and deploying machine learning models in production Proficiency in Python Nice‑to‑Have Experience partnering with trust & safety leads and background in trust & safety, moderation, AI safety, or security‑focused ML to deliver state‑of‑the‑art solutions [a big plus] An advanced degree in computer science or a related field LLM and agentic framework experience Experience in early‑stage startups Experience in customer‑facing AI technical solutions Contributions to high value AI/ML community projects Who We Are Reinforce Labs is a small team with a clear mission: to use AI to make critical systems safer, not just smarter. We value: Willingness to learn new things, take on diverse tasks, and challenge yourself Hands‑on technical excellence Ownership Ability to handle ambiguity Fast, results‑driven delivery #J-18808-Ljbffr