Systems administrator jobs in Berkeley, CA - 1,720 jobs

A leading technology company is looking for a Machine Learning Infrastructure Engineer in Sunnyvale, California. You will develop data ecosystems and infrastructure for ML projects, partnering closely with engineers and scientists. Candidates should have a Bachelor's in Computer Science and experience with cloud providers, as well as strong programming skills in Python. This is an opportunity to be a part of innovative projects that influence the next generation of technology. #J-18808-Ljbffr

A leading financial institution seeks a Market Executive in San Francisco to manage relationships within the Software Technology sector and lead banking teams. The candidate will focus on innovative startups and require 15+ years of experience in account management within a Commercial Bank. This role also demands strong communication and problem-solving skills. A competitive salary and benefits are offered for this full-time position, with an emphasis on industry trends and client acquisition. #J-18808-Ljbffr

A technology industry leader in California is seeking a Product Definition Engineer to evaluate and optimize pre-production silicon. The successful candidate will work with multi-functional teams, driving new feature initiatives and designing performance-critical product features. Ideal candidates will have significant engineering experience and collaborative skills. The role offers a salary range of 168,000 - 264,500 USD depending on level, alongside equity and benefits. #J-18808-Ljbffr

About Us: Ambience Healthcare is the leading AI platform for documentation, coding, and clinical workflow, built to reduce administrative burden and protect revenue integrity at the point of care. Trusted by top health systems across North America, Ambience's platform is live across outpatient, emergency, and inpatient settings, supporting more than 100 specialties with real-time, coding‑aware documentation. The platform integrates directly with Epic, Oracle Cerner, athenahealth, and other major EHRs. Founded in 2020 by Mike Ng and Nikhil Buduma, Ambience is headquartered in San Francisco and backed by Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, Kleiner Perkins, and other leading investors. Join us in the endeavor of accelerating the path to safe & useful clinical super intelligence by becoming part of our community of problem solvers, technologists, clinicians, and innovators. The Role: We're looking for a Machine Learning Infrastructure Engineer to join our AI Platform team. This is a high-leverage role focused on building and scaling the core infrastructure that powers every AI system at Ambience. You'll work closely with our ML, data, and product teams to develop the foundational tools, systems, and workflows that support rapid iteration, robust evaluation, and production reliability for our LLM‑based products. Our engineering roles are hybrid - working onsite at our San Francisco office three days per week. What You'll Do: You have 5+ years of experience as a software engineer, infrastructure engineer, or ML platform engineer You've worked directly on systems that support ML research or production workloads - whether training pipelines, evaluation systems, or deployment frameworks You write high-quality code (we primarily use Python) and have strong engineering and systems design instincts You're excited to work closely with ML researchers and product engineers to unblock them with better infrastructure You're pragmatic and care deeply about making tools that are reliable, scalable, and easy to use You thrive in fast-paced, collaborative environments and are eager to take ownership of ambiguous problems Who You Are: Design, build, and maintain the infrastructure powering ML model training, batch inference, and evaluation workflows Improve internal tools and developer experience for ML experimentation and observability Partner with ML engineers to optimize model deployment and monitoring across clinical workloads Define standards for model versioning, performance tracking, and rollout processes Collaborate across the engineering team to build reusable abstractions that accelerate AI product development Drive performance, cost efficiency, and reliability improvements across our AI infrastructure stack Pay Transparency We offer a base compensation range of approximately $200,000-300,000 per year, with the addition of significant equity. This intentionally broad range provides flexibility for candidates to tailor their cash and equity mix based on individual preferences. Our compensation philosophy prioritizes meaningful equity grants, enabling team members to share directly in the impact they help create. If your expectations fall outside of this range, we still encourage you to apply-our approach to compensation considers a range of factors to ensure alignment with each candidate's unique needs and preferences. Being at Ambience: An opportunity to work with cutting edge AI technology, on a product that dramatically improves the quality of life for healthcare providers and the quality of care they can provide to their patients Dedicated budget for personal development, including access to world class mentors, advisors, and an in‑house executive coach Work alongside a world‑class, diverse team that is deeply mission aligned Ownership over your success and the ability to significantly impact the growth of our company Competitive salary and equity compensation with benefits including health, dental, and vision coverage, quarterly retreats, unlimited PTO, and a 401(k) plan Ambience is committed to supporting every candidate's ability to fully participate in our hiring process. If you need any accommodations during your application or interviews, please reach out to our Recruiting team at accommodations@ambiencehealth.com. We'll handle your request confidentially and work with you to ensure an accessible and equitable experience for all candidates. #J-18808-Ljbffr

A leading AI infrastructure company in San Francisco seeks an experienced engineer to build and improve core ML systems for training custom AI models. The role requires 2+ years of experience in training AI models, proficiency in PyTorch, and familiarity with NVIDIA GPUs. Responsibilities include leading projects from data intake through the full training pipeline, building data processing systems, and creating visualization tools. Competitive salary ranging from $220K to $320K plus equity and benefits offered. #J-18808-Ljbffr

Principal Enterprise IT Engineer, IT & Security About 1X We're an AI and robotics company based in Palo Alto, California, on a mission to build a truly abundant society through general-purpose robots capable of performing any kind of work autonomously. We believe that to truly understand the world and grow in intelligence, humanoid robots must live and learn alongside us. That's why we're focused on developing friendly home robots designed to integrate seamlessly into everyday life. We're looking for curious, driven, and passionate people who want to help shape the future of robotics and AI. If this mission excites you, we'd be thrilled to hear from you and explore how you might contribute to our journey. Role Overview The Principal Enterprise IT Engineer will lead the strategy, architecture, and implementation of enterprise IT systems across the company. This role will define standards for identity, endpoint management, collaboration, and security while scaling IT infrastructure to support rapid organizational growth. You'll play a key leadership role, mentoring senior engineers and influencing cross-functional and executive stakeholders to align IT operations with strategic business needs. Responsibilities Define and drive enterprise IT strategy, architecture, and roadmaps across identity, collaboration, and device platforms Lead administration and scaling of Google Workspace, Okta, Intune, and MDM platforms with a focus on Zero Trust principles Develop and implement automation frameworks and scripting (Bash, Python, PowerShell) to streamline IT operations Align IT systems with compliance standards (e.g., SOC2, ISO 27001) and proactively mitigate enterprise risks Ensure seamless integration of IT systems with engineering, manufacturing, and robotics environments Act as senior escalation point for IT operations, mentoring IT engineers and building a high-performance function Influence executive and cross-functional stakeholders to ensure IT strategy supports business growth Requirements Expert-level knowledge of Google Workspace, Okta, Microsoft Intune, and MDM platforms across multiple OS (mac OS, Windows, iOS, Android) Strong scripting and automation skills (Bash, Python, PowerShell); experience implementing Zero Trust security Proven experience scaling IT systems globally in high-growth, cloud-first or hybrid environments Ability to lead IT architecture initiatives and partner with executive and security leadership Experience mentoring senior IT engineers and leading high-performance teams Preferred: Familiarity with Terraform, Ansible, and IT support for robotics or engineering-heavy environments Preferred: Certifications such as CISSP, Okta Certified Architect, Google Workspace Admin, or Microsoft Enterprise Mobility Benefits & Compensation Salary Range: $180,000 - $235,000 Health, dental, and vision insurance 401(k) with company match Paid time off and holidays Equal Opportunity Employer 1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, or any other characteristic protected under applicable federal, state, or local law. #J-18808-Ljbffr

A pioneering AI startup in San Francisco is looking for an experienced individual to build infrastructure for deploying personalized AI models. The role demands a strong understanding of machine learning technology and a passion for enabling user-controlled AI solutions. Ideal candidates will thrive in fast-paced environments and contribute to impactful AI development. The company offers competitive compensation, equity, and a significant role in shaping the future of AI. #J-18808-Ljbffr

David AI is the first audio data research company. We bring an R&D approach to data-developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human-it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in. David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we've brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors. Our team is sharp, humble, ambitious, and tight-knit. We're looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI. About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world's first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As our Founding Machine Learning Infrastructure Engineer at David AI, you will build and scale the core infrastructure that powers our cutting-edge audio ML products. You'll be leading the development of the systems that enable our researchers and engineers to train, deploy, and evaluate machine learning models efficiently. In this role, you will Design and maintain data pipelines for processing massive audio datasets, ensuring terabytes of data are managed, versioned, and fed into model training efficiently. Develop frameworks for training audio models on compute clusters, managing cloud resources, optimizing GPU utilization, and improving experiment reproducibility. Create robust infrastructure for deploying ML models to production, including APIs, microservices, model serving frameworks, and real-time performance monitoring. Apply software engineering best practices with monitoring, logging, and alerting to guarantee high availability and fault‑tolerant production workloads. Translate research prototypes into production pipelines, working with ML engineers and data teams to support efficient data labeling and preparation. and optimization techniques to enhance infrastructure velocity and reliability. Your background looks like 5+ years of backend engineering with 2+ years ML infrastructure experience. Hands‑on experience scaling cloud infrastructure and large‑scale data processing pipelines for ML model training and evaluation. Proficient with Docker, Kubernetes, and CI/CD pipelines. Proven ML model deployment and lifecycle management in production. Strong system design skills optimizing for scale and performance. Proficient in Python with deep Kubernetes experience. Bonus points if you have Experience with feature stores, experiment tracking (MLflow, Weights and Biases), or custom CI/CD pipelines. Familiarity with large‑scale data ingestion and streaming systems (Spark, Kafka, Airflow). Proven ability to thrive in fast‑moving startup environments. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Benefits Unlimited PTO. Top‑notch health, dental, and vision coverage with 100% coverage for most plans. FSA & HSA access. 401k access. Meals 2x daily through DoorDash + snacks and beverages available at the office. Unlimited company‑sponsored Barry's classes. #J-18808-Ljbffr

This is a job that we are recruiting for on behalf of one of our customers. To apply, speak to Jack. He's an AI agent that sends you unmissable jobs and then helps you ace the interview. He'll make sure you are considered for this role, and help you find others if you ask. Machine Learning Infrastructure Engineer Company Description: Early-stage private AI platform Job Description: Build the core infrastructure to serve thousands, then millions, of private, personalized AI models at scale. This role involves optimizing model serving performance for low latency and cost, and integrating a TEE-based privacy stack to ensure user data and models are exclusively accessible by the user, not even the company. Drive the foundational systems for a new era of personal AI. Location: San Francisco, USA Why this role is remarkable: Pioneer the infrastructure for truly private, personal AI models, ensuring user data remains confidential. Join an early-stage, well-funded startup backed by top-tier VCs and leading AI experts. Make a massive impact on the future of AI, helping to keep humans empowered in a post-AGI world. What you will do: Build infrastructure for deploying thousands to millions of personalized finetuned models. Monitor and optimize in-the-wild model serving performance for low latency and cost. Integrate with a TEE-based privacy stack to guarantee user data and model confidentiality. The ideal candidate: Deep understanding of the machine learning stack, including transformer optimization and GPU performance. Ability to execute quickly in a fast-paced, early-stage startup environment. A missionary mentality, passionate about ensuring AI works for people. How to Apply: To apply for this job speak to Jack, our AI recruiter. Step 1. Visit our website Step 2. Click 'Speak with Jack' Step 3. Login with your LinkedIn profile Step 4. Talk to Jack for 20 minutes so he can understand your experience and ambitions Step 5. If the hiring manager would like to meet you, Jack will make the introduction #J-18808-Ljbffr

A leading productivity company is seeking a Business Systems Engineer to enhance its systems and integrations. The ideal candidate has 4-6 years of experience, strong Salesforce development expertise, and programming proficiency. This hybrid role involves collaboration with various teams to streamline processes and improve data flow. Competitive compensation in San Francisco is offered, with a salary range of $190,000-$215,000 annually. #J-18808-Ljbffr

A pioneering tech company in San Francisco is seeking a Robotics Engineer who excels in system-level debugging and end-to-end feature delivery for autonomous trucks. The successful candidate will develop and validate autonomy features, lead technical deployments, and collaborate across various teams. Requirements include 2+ years of software development experience and strong programming skills in modern languages. A role involving occasional travel to customer sites is also included. #J-18808-Ljbffr

A fast-growing tech company based in San Francisco seeks an experienced IT Engineer for contract work. You will manage IT operations, leading employee onboarding and troubleshooting. Candidates should have 3-5 years of experience in IT roles, with skills in Google Workspace and troubleshooting. The position requires reliable execution and communication skills. You will work in the office three days a week, participating in an innovative tech culture that values diversity and collaboration. #J-18808-Ljbffr

A leading research lab in Sunnyvale is seeking a distributed ML infrastructure engineer to extend and scale training systems. The ideal candidate must have over 5 years of experience in ML systems with strong expertise in distributed training frameworks like DeepSpeed and FSDP. This role offers a competitive salary ranging from $150,000 to $450,000 annually along with comprehensive benefits and amenities. #J-18808-Ljbffr

About the Team OpenAI's Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI's supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're seeking a Networking Operating System Firmware Engineer to help bootstrap and scale the switching layer of our AI supercomputers. In this role, you'll build and maintain custom SONiC NOS images from scratch, working across the Linux kernel, switch ASIC SAI/SDKs, platform drivers, control-plane services, and orchestration layers. You will validate, configure, and optimize switch platforms used across our high-bandwidth cluster fabric, ensuring performance, reliability, availability, and seamless integration with fleet automation. You'll collaborate with hardware and systems teams and guide vendors to meet stringent technical expectations. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, develop, and maintain custom SONiC NOS images for large-scale bleeding-edge AI fabrics. Integrate and configure Linux kernel components, device drivers, switch ASIC SDKs, and SAI layers. Bring up new switch platforms (thermal/fan control, power monitoring, transceiver management, watchdogs, OSFP CMIS, LEDs, CPLDs, etc.). Extend and customize SONiC services for routing, telemetry, control-plane state, and distributed automation. Work with hardware teams to validate ASIC configurations, link bring-up, SerDes tuning, buffer profiles, and performance baselines. Evaluate switch silicon SDK releases, track vendor deliverables, and define platform requirements with vendors and ASIC partners. Debug complex issues spanning kernel, platform drivers, SONiC dockers, routing agents, orchestration services, hardware signals, and network topology. Integrate switches into fleet-wide monitoring, remote diagnostics, telemetry pipelines, and automated lifecycle workflows. Develop robust CI/build pipelines for reproducible NOS builds and controlled rollout across the fleet. Support factory bring-up and qualification all the way through mass deployment. Collaborate, architect, implement, and deploy novel networking protocols and technologies to achieve maximum performance and reliability at AI factory scale. You might thrive in this role if you: Proven experience working with SONiC or comparable NOS stacks (FBOSS, Cumulus Linux, Arista EOS, Junos PFE-level integration, etc.). Experience with updating OpenConfig gNMI interfaces and YANG data models. Strong background in Linux kernel, network device drivers, and low-level OS internals. Experience integrating Broadcom / Marvell / NVIDIA / Intel ASIC SDKs and SAI implementations. Proficiency in C, C++ and Python; familiarity with Rust/Go is a plus. Deep understanding of L2/L3 forwarding, ECMP, RoCE, BGP, QoS, PFC, buffer tuning, and telemetry. Hands‑on experience with hardware platform bring‑up and board‑level debugging. Familiarity with CI/CD pipelines, distributed config/state management, and large‑scale automation. Strong cross‑functional problem solving in high‑performance, distributed environments. Ability to lead teams to deliver a project end to end. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general‑purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI's Aff… Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US‑based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non‑public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non‑compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. #J-18808-Ljbffr

A technology company in San Francisco is looking for a candidate to own the end-to-end lifecycle of memory features including fine-tuning models and conducting evaluations. You will work closely with customers to identify pain points and collaborate with engineering to implement solutions. The ideal applicant will have experience in information retrieval, model training, and communication with stakeholders. This role requires strong skills in Python and familiarity with machine learning frameworks like PyTorch. The company offers a dynamic and innovative work environment. #J-18808-Ljbffr

A cutting-edge CRM startup based in San Francisco seeks a Recruiting Manager to lead the hiring of exceptional engineering talent. You will develop innovative recruitment strategies and enhance the company's employer brand, ensuring a smooth candidate experience from start to finish. Ideal candidates have extensive recruiting experience with a focus on engineering roles and possess a comprehensive understanding of modern software technologies. Join us in building a transformative CRM platform. #J-18808-Ljbffr

A technology firm focused on AI safety is seeking a candidate for a mission-driven role that melds engineering with customer empathy. You will be responsible for leading client integrations of trust and safety software, ensuring successful product adoption while also translating client feedback into actionable improvements. This in-person role is based in San Francisco and includes regular travel across the U.S. Competitive salary and equity are offered. #J-18808-Ljbffr

Build the infrastructure to serve personal AI models privately and at scale. We're building the first truly private, personal AI - one that learns your skills, judgment, and preferences without big tech ever seeing your data. Our core ML systems challenge: how do we serve the world's best personal model, at low cost and high speed, with bulletproof privacy? What you'll do Build the infrastructure that lets us create & deploy thousands and eventually millions of personalized finetuned models for our customers Monitor & optimize in-the-wild model serving performance to hit low latency & cost Interface with the TEE-based privacy stack that lets us guarantee user data & models can only be seen & used by the user-not even us-and integrate the privacy architecture with the finetuning & inference code You have A deep understanding of the machine learning stack. You can dive into the details of how transformers work & performance optimization techniques for them. You have a mental model of GPUs sufficient to reason about performance from first principles. You can drill down from ML code to metal. Ability to execute quickly. We ship fast and fail fast so we can win faster. The challenge of human relevance in a post-AGI world isn't going to solve itself. A missionary mentality. We're a mission-driven company, looking for mission-first people. If you're passionate about ensuring AI works for people (and not the other way around), you've come to the right place. Ready to roll up your sleeves. We're an early stage startup, so we're looking for someone who can wear many hats. Experience you may have Work at a fast-paced AI startup, or top AI lab Experience deploying ML systems at scale. You might have worked with frameworks like vLLM, S-LoRA, Punica, or LoRAX. Experience with privacy-first infrastructure. You're familiar with confidential computing & ability to reason about both technical and real-world confidentiality and security. You may have worked with secure enclaves, TEEs, code measurement & remote attestation, Nvidia Confidential Computing, Intel TDX or AMD SEV-SNP, or related confidential computing technologies. We encourage speculative applications; we expect many strong candidates will have different experience or unconventional backgrounds. What we offer Generous compensation and early stage equity. We're competitive with the top startups, because we believe the best talent deserves it. World-class expertise. We're based in top AI research hubs in San Francisco and London. We're backed by AI experts like Juniper Ventures, Seldon Lab, and angels at Anthropic and Apollo Research. You'll have access to some of the best AI expertise in the world. Massive impact. Our mission is to keep people in the economy well after AGI. You'll help shift the trajectory of AI development for the better, helping break the intelligence curse and prevent gradual disempowerment to keep humans in control of the future. About Workshop Labs We're building the AI economy for humans. While everyone else tries to automate the world top-down, we believe in augmenting people bottom-up. Our team previously created evals used by Open AI, completed frontier AI research at MIT/Cambridge/Oxford, worked in Stuart Russell's lab, and led product verticals at high growth startups. The essay series The Intelligence Curse has been covered in TIME, The New York Times, and AI 2027. Our vision is for everyone to have a personal AI aligned to their goals and values, helping them stay durably relevant in a post-AGI economy. As a public benefit corporation, we have a fiduciary duty to ensure that as AI becomes more powerful, humans become more empowered, not disempowered or replaced. We're an early stage startup, backed by legendary investors like Brad Burnham and Matt McIlwain, visionary product leaders like Jake Knapp and John Zeratsky, philosopher-builders like Brendan McCord, and top AI safety funds like Juniper Ventures. Our investors were early at Anthropic, Slack, Prime Intellect, DuckDuckGo, and Goodfire. Our advisors have held senior roles at Anthropic, Google DeepMind, and UK AISI. #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 We're looking for a distributed ML infrastructure engineer to help extend and scale our training systems. You'll work side‑by‑side with world‑class researchers and engineers to: Extend distributed training frameworks (e.g., DeepSpeed, FSDP, FairScale, Horovod) Implement distributed optimizers from mathematical specs Build robust config + launch systems across multi‑node, multi‑GPU clusters Own experiment tracking, metrics logging, and job monitoring for external visibility Improve training system reliability, maintainability, and performance While much of the work will support large‑scale pre‑training, pre‑training experience is not required. Strong infrastructure and systems experience is what we value most. Key Responsibilities Distributed Framework Ownership - Extend or modify training frameworks (e.g., DeepSpeed, FSDP) to support new use cases and architectures. Optimizer Implementation - Translate mathematical optimizer specs into distributed implementations. Launch Config & Debugging - Create and debug multi‑node launch scripts with flexible batch sizes, parallelism strategies, and hardware targets. Metrics & Monitoring - Build systems for experiment tracking, job monitoring, and logging usable by collaborators and researchers. Infra Engineering - Write production‑quality code and tests for ML infra in PyTorch or JAX; ensure reliability and maintainability at scale. Qualifications Must-Haves: 5+ years of experience in ML systems, infra, or distributed training Experience modifying distributed ML frameworks (e.g., DeepSpeed, FSDP, FairScale, Horovod) Strong software engineering fundamentals (Python, systems design, testing) Proven multi‑node experience (e.g., Slurm, Kubernetes, Ray) and debugging skills (e.g., NCCL/GLOO) Ability to implement algorithms across GPUs/nodes based on mathematical specs Experience working on an ML platform/ infrastructure, and/or distributed inference optimization team Experience with large‑scale machine learning workloads (strong ML fundamentals) Nice-to-Haves: Exposure to mixed‑precision training (e.g., bf16, fp8) with accuracy validation Familiarity with performance profiling, kernel fusion, or memory optimization Open‑source contributions or published research (MLSys, ICML, NeurIPS) CUDA or Triton kernel experience Experience with large‑scale pre‑training Experience building custom training pipelines at scale and modifying them for custom needs Deep familiarity with training infrastructure and performance tuning $150,000 - $450,000 a year Benefits Comprehensive medical, dental, and vision 401(k) program Generous PTO, sick leave, and holidays Paid parental leave and family‑friendly benefits On‑site amenities and perks: Complimentary lunch, gym access, and a short walk to the Sunnyvale Caltrain station #J-18808-Ljbffr