ML Engineer - Embodied AI Scaling Foundations

Job Description

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.

• 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 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.

• 5+ years of experience building large‑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.
• End‑to‑end experience across the ML development lifecycle, including MLOps practices.
• Strong cross‑functional collaboration skills across teams and organizations.
• Proficiency with containerization and orchestration technologies (e.g., Docker, Kubernetes).
• 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.

• 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, Tensor Flow).
• Experience with performance profiling and state‑of‑the‑art training optimization techniques, including their impact on model convergence.
• Experience with advanced build systems (e.g., Bazel, Buck, Blaze, CMake).

This role is categorized as hybrid. This means the successful candidate is expected to report to the Sunnyvale or Mountain View Technical Center in the Bay Area three times per week, at minimum.

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 $189,000 to $300,000. 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.

• 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.

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.

This job may be eligible for relocation benefits.

Our 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.

We believe we all must…