GE Senior ML Infrastructure Engineer - Embodied AI Generalmotors · Remote · US · ML Platform & Ops $153,200–$234,100 6mo ago

Aimlroles; Northern (KY); Hybrid; USD 153,000 - 234,000; Full time

Benefits offered by this job

Relocation benefits

Vehicle discounts

Comprehensive benefits package

Job summary

General Motors' Embodied AI team is accelerating autonomous driving by building scalable ML platforms and reliable deployment workflows. You will design and deploy pipelines, drive complex ML projects with strong ownership, and collaborate across GM to optimize platform adoption and performance.

You’ll contribute to a culture of high-quality code, mentorship for juniors, and cross-functional teamwork to deliver safe, scalable autonomous capabilities at scale.

Qualifications

• 3+ years of experience working on large-scale distributed systems, applications, or ML infrastructure.
• Experience designing robust services or frameworks with durable APIs.
• Solid understanding of machine learning workflows and hands-on production ML deployments.
• Experience building reliable, high-performance systems on cloud infrastructure.
• Proficiency with Python or C++ and exposure to ML development lifecycle (training, deployment, MLOps).
• Strong cross-functional collaboration and ability to work with multiple teams.

Responsibilities

• Design, implement, and deploy scalable platforms and tools for ML training and evaluation across GM.
• Drive complex technical projects with ownership of implementation, code quality, and reliability.
• Participate in design discussions and architectural decisions with senior engineers and leads.
• Collaborate with partner teams to meet real-world ML development needs and maximize adoption.
• Identify improvements and prioritize platform investments to boost performance and developer productivity.
• Foster engineering culture through code reviews, documentation, and operational excellence.
• Support onboarding and mentoring of junior engineers and interns.

Skills

Distributed systems

APIs design

ML workflows

Python

C++

Cloud infrastructure

Collaboration

MLOps

Education

BS/MS/PhD in CS/Math

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Bazel/Buck/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.

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 experienceworking onlarge-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, andMLOpspractices.
• Strong cross-functional collaboration skills across teams and organizations.
• Strong coding skills in Python or C++.
• Interestin 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 asPyTorchor 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, orCMake.
• Proficiencywith 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.)

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.

To learn more, visit How we Hire.

Accommodations

General 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, emailus 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.