Staff ML Infrastructure Engineer - Embodied AI Scaling Foundations
General Motors
Staff ML Infrastructure Engineer - Embodied AI Scaling Foundations
Job Description
Job DescriptionAt General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Role:Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.As a Staff ML Infra Engineer, you will drive the development of core systems that enable rapid dataset generation, training, evaluation, and iteration of our most advanced Autonomous Driving models. From enabling large foundational driving models to distilling multi-stage production deployed models, your goal will be to dramatically accelerate the machine learning development cycle from one modeling hypothesis to next. You will deliver model training pipelines that are performant, easy to use, and exceptionally reliable. Your success will be measured by the velocity and impact of the ML models that rely on the scalable, intuitive, and high‑performance training platforms you help create. What you'll do:Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM. Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. You will be a core contributor to team planning, design reviews, and code quality. Take a holistic view of projects, considering their impact across multiple teams, and across a longer timeline. Proactively drive technical prioritization. Collaborate closely with partner teams to ensure maximum benefit from the systems we build. Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting. Mentor and onboard junior engineers and interns, helping them grow their careers. What you'll bring:5+ years of experience building large-scale distributed systems, applications, or advanced ML systems‑scale distributed systems, applications, or advanced ML systems Proven track record of designing robust frameworks with high-quality, durable APIs. Deep understanding of machine learning algorithms with hands‑on application Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure‑performance End-to-end experience across the ML development lifecycle, including MLOps practices Strong cross functional collaboration skills across teams and organizations Exceptional coding skills in Python or C++ Strong interest in autonomous driving and its transformative potential BS, MS, or PhD in Computer Science, Mathematics, or equivalent practical experience Nice to have:Experience with distributed training methodologies Experience scaling ML training across large GPU/CPU clusters or other accelerators Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) Experience with performance profiling and state-of-the-art training optimization techniques, including their impact on model performance ‑of‑the‑art training optimization techniques, including their impact on convergence. Experience with advanced build systems (e.g., Bazel, Buck, Blaze, CMake) Proficiency with containerization and orchestration technologies (e.g., Docker, Kubernetes) Remote/Hybrid: This role is categorized as fully remote or hybrid.Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area. The salary range for this role is $189,300.00 to $290,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. Relocation: This job may be eligible for relocation benefits. Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.#GM-AV-1#LI-CX1
About GMOur vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.Benefits OverviewFrom day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.Non-Discrimination and Equal Employment Opportunities (U.S.)General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.AccommodationsGeneral Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
Locations
- United States of America, California, Sunnyvale
Skills Required
- large-scale distributed systemsintermediate
- building reliableintermediate
- distributed training methodologiesintermediate
- deep learning frameworksintermediate
- performance profilingintermediate
- advanced build systemsintermediate
- containerizationintermediate
Required Qualifications
- 5+ years of experience building large-scale distributed systems, applications, or advanced ML systems‑scale distributed systems, applications, or advanced ML systems (experience, 5 years)
- 5+ years of experience building large-scale distributed systems, applications, or advanced ML systems‑scale distributed systems, applications, or advanced ML systems (experience, 5 years)
- Proven track record of designing robust frameworks with high-quality, durable APIs. (experience)
- Proven track record of designing robust frameworks with high-quality, durable APIs. (experience)
- Deep understanding of machine learning algorithms with hands‑on application (experience)
- Deep understanding of machine learning algorithms with hands‑on application (experience)
- Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure‑performance (experience)
- Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure‑performance (experience)
- End-to-end experience across the ML development lifecycle, including MLOps practices (experience)
- End-to-end experience across the ML development lifecycle, including MLOps practices (experience)
- Strong cross functional collaboration skills across teams and organizations (experience)
- Strong cross functional collaboration skills across teams and organizations (experience)
- Exceptional coding skills in Python or C++ (experience)
- Exceptional coding skills in Python or C++ (experience)
- Strong interest in autonomous driving and its transformative potential (experience)
- Strong interest in autonomous driving and its transformative potential (experience)
- BS, MS, or PhD in Computer Science, Mathematics, or equivalent practical experience (experience)
- BS, MS, or PhD in Computer Science, Mathematics, or equivalent practical experience (experience)
Preferred Qualifications
- Experience with distributed training methodologies (experience)
- Experience with distributed training methodologies (experience)
- Experience scaling ML training across large GPU/CPU clusters or other accelerators (experience)
- Experience scaling ML training across large GPU/CPU clusters or other accelerators (experience)
- Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) (experience)
- Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) (experience)
- Experience with performance profiling and state-of-the-art training optimization techniques, including their impact on model performance ‑of‑the‑art training optimization techniques, including their impact on convergence. (experience)
- Experience with performance profiling and state-of-the-art training optimization techniques, including their impact on model performance ‑of‑the‑art training optimization techniques, including their impact on convergence. (experience)
- Experience with advanced build systems (e.g., Bazel, Buck, Blaze, CMake) (experience)
- Experience with advanced build systems (e.g., Bazel, Buck, Blaze, CMake) (experience)
- Proficiency with containerization and orchestration technologies (e.g., Docker, Kubernetes) (experience)
- Proficiency with containerization and orchestration technologies (e.g., Docker, Kubernetes) (experience)
- Remote/Hybrid: This role is categorized as fully remote or hybrid. (experience)
- Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area. (experience)
- The salary range for this role is $189,300.00 to $290,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. (experience)
- The salary range for this role is $189,300.00 to $290,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. (experience)
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. (experience)
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. (experience)
Responsibilities
- Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM.
- Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM.
- Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. You will be a core contributor to team planning, design reviews, and code quality.
- Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. You will be a core contributor to team planning, design reviews, and code quality.
- Take a holistic view of projects, considering their impact across multiple teams, and across a longer timeline.
- Take a holistic view of projects, considering their impact across multiple teams, and across a longer timeline.
- Proactively drive technical prioritization. Collaborate closely with partner teams to ensure maximum benefit from the systems we build.
- Proactively drive technical prioritization. Collaborate closely with partner teams to ensure maximum benefit from the systems we build.
- Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting.
- Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting.
- Mentor and onboard junior engineers and interns, helping them grow their careers.
- Mentor and onboard junior engineers and interns, helping them grow their careers.
Benefits
- general: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
- general: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
- general: Relocation: This job may be eligible for relocation benefits.
- general: Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
- general: From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
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