Senior ML Infrastructure Engineer - Embodied AI

General Motors; Washington; Hybrid; USD 153,000 - 234,000; Full time

Benefits offered by this job

Bonus potential

Relocation benefits

Job summary

General Motors is seeking a Senior MLInfra Engineer to accelerate autonomous driving with scalable ML training and deployment platforms. You’ll build high-performance pipelines and tools enabling rapid dataset generation, training, and evaluation across GM's autonomous driving programs.

The role emphasizes robust APIs, cloud-based infrastructure, and collaboration with senior engineers to deliver reliable, scalable ML systems. Remote or hybrid work options are available, within the United States.

Qualifications

• 3+ years on large-scale distributed systems or ML infrastructure.
• Experience designing robust services with durable APIs.
• Hands-on ML workflows in production environments.
• Experience building scalable cloud-based systems.
• Experience with ML development lifecycle: training, deployment, MLOps.
• Strong cross-functional collaboration.

Responsibilities

• Design, implement, and deploy scalable ML training and evaluation platforms.
• Drive complex technical projects with ownership of implementation and reliability.
• Contribute to architectural decisions with senior engineers.
• Collaborate with partner teams to meet ML development needs.
• Mentor junior engineers and interns.
• Ensure high-quality code reviews and documentation.

Skills

Distributed systems

APIs design

Python or C++

Cloud infrastructure

ML infrastructure

Education

BS/MS/PhD in Computer Science or Mathematics

Tools

Docker

Kubernetes

PyTorch

TensorFlow

CMake

Job description

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’returningtoday’simpossible 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 peopleas we aim to makedriving 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 Senior MLInfra Engineer, you will work on the 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 develop 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:

• Design, implement, and deploy scalable platforms and tools supporting machine learning training and evaluation workflows across GM.

• Drive complex technical projects with strong ownership of implementation, code quality, and system reliability.

• Contribute to technical design discussions and architectural decisions while collaborating with senior engineers and technical leads.

• Work closely with partner teams to ensure platforms meet real-world ML development needs and maximize adoption.

• Identify technical improvements and help prioritize platform investments to improve performance, reliability, and developer productivity.

• Contribute to a strong engineering culture through high‑quality code reviews, documentation, and operational excellence.

• Support onboarding and mentoring of junior engineers and interns.

What You’ll Bring:

• 3+ years of experience working on large-scale distributed systems, applications, or ML infrastructure.

• Experience designing robust services or frameworks with durable, well-designed APIs.

• Solid understanding of machine learning workflows and hands‑on experience applying ML systems in production environments.

• Experience building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure.

• Practical experience across the ML development lifecycle, including model training, deployment, and MLOps practices.

• Strong cross-functional collaboration skills across teams and organizations.

• Strong coding skills in Python or C++.

• Interest in autonomous driving and large-scale ML systems.

• 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 specialized accelerators.

• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.

• Experience with performance profiling and training optimization techniques and their impact on model convergence and performance.

• Experience with advanced build systems such as Bazel, Buck, Blaze, or 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 paidin accordance withapplicable state laws. The compensation may not be representative for positionslocatedoutside of the California Bay Area.

• The salary range for this role is $153,200.00 to $234,100.00. 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 incentivepayprogram offers payouts based on company performance, job level, and individual performance.

Benefits:

• 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, tuitionassistanceprograms, employeeassistanceprogram, GM vehicle discounts and more.

This job may be eligible forrelocationbenefits.

About GM

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.

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 Overview

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.

Non-Discrimination and Equal Employment Opportunities (U.S