Staff ML Infrastructure Engineer - Embodied AI Scaling Foundations

General Motors; United States; Hybrid; USD 172,000 - 335,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Relocation assistance

Job summary

General Motors seeks a Staff ML Infra Engineer to accelerate autonomous driving by building scalable model training and evaluation platforms. You will own end-to-end, design robust systems, and mentor junior engineers while collaborating across GM teams.

The role offers remote or hybrid work in the United States, with compensation applicable to the Bay Area range and a strong incentive program. Bring advanced ML expertise to a transformative mobility project.

Qualifications

• 5+ years building large-scale distributed systems or ML platforms.
• Robust API design and high-quality software engineering.
• Hands-on ML knowledge and cloud experience.
• End-to-end ML lifecycle and MLOps practices required.
• Strong cross-functional collaboration and coding in Python/C++.
• Background in autonomous driving is highly valued.

Responsibilities

• Lead design and deployment of scalable ML training/evaluation platforms.
• Own complex projects end-to-end with architectural trade-offs.
• Collaborate across teams to maximize system impact.
• Contribute to technical interviews and recruit junior staff.
• Mentor engineers and interns to grow their careers.

Skills

Distributed systems

API design

ML systems

Cloud infrastructure

MLOps

Cross-functional collaboration

Python or C++

Autonomous driving interest

Academic credentials (CS/Math)

Education

BS, MS, or PhD in Computer Science or Mathematics

Tools

Docker

Kubernetes

Bazel

Buck

CMake

PyTorch

TensorFlow

Job description

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 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 foundation level 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.

Skills & Abilities (Required Qualifications)

• 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

Exceptional candidates may also 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)
• 5+ years of professional experience

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 $171,700.00 to $335,300.00. 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 rel