Staff ML Infrastructure Engineer - Embodied AI

General Motors • Mountain View, CA

1d • Hybrid

About The Position

At 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 Engineer, you will build critical infrastructure that powers every machine learning engineer working on our cutting-edge Autonomous Driving models. From foundational models to state-of-the-art optimization, our goal is simple: dramatically accelerate the machine learning development cycle. We are committed to delivering products that are performant, easy to use, and exceptionally reliable. Your success will be measured by the success of our partner teams who rely on our robust systems to build the world's most advanced driverless vehicles.

Requirements

• 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‑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, and cost‑efficient systems on modern cloud infrastructure
• End-to-end experience across the ML development lifecycle, including MLOps practices‑to‑end experience across the ML development lifecycle, including
• Strong cross functional collaboration skills across teams and organizations‑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

Nice To Haves

• 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)

Responsibilities

• 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.

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.
• This job may be eligible for relocation benefits.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level