Staff AI / ML Engineer - Embodied AI

generalmotors; Mountain View (CA); Hybrid; USD 219,000 - 335,000; Full time

Benefits offered by this job

Health benefits

GM vehicle discounts

Relocation benefits

Job summary

General Motors seeks a Staff AI/ML Engineer in the Embodied AI group to develop and deploy machine learning solutions that enhance autonomous driving performance. You will design advanced ML models for safe, reliable vehicle behavior across diverse real-world scenarios.

You will mentor engineers, translate research into scalable onboard systems, and drive production deployment from prototyping to deployment while collaborating with cross-functional teams.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Machine Learning, or related field.
• Experience with large-scale foundation models and alignment methods in real-world systems.
• Proficiency in PyTorch and Python; experience building training pipelines and data processing with NumPy/Pandas/Spark.

Responsibilities

• Design and implement ML solutions aligned with GM’s autonomous driving objectives.
• Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, and model scaling.
• Collaborate with cross-functional teams to deploy models into onboard driving systems.
• Contribute to applied research and stay current with ML frameworks and methods.
• Design and build infrastructure, pipelines, and tooling for fast model iteration.
• Drive from prototyping to production deployment and document learnings.

Skills

PyTorch

Python

NumPy

Pandas

Apache Spark

Education

Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Machine Learning

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

As a Staff AI/ML Engineer in the Embodied AI organization, you will serve as a senior individual contributor developing and deploying machine learning solutions that directly impact autonomous driving performance. You will design and implement advanced ML models that enable safe and reliable vehicle behavior across diverse real-world scenarios.

In this role, you will partner closely with cross-functional engineering teams, contribute to core technical direction within your domain, and support the growth of engineers through technical collaboration and mentorship. You will help translate research into scalable onboard ML solutions while contributing to the continuous improvement of our autonomy stack.

What You'll Do

• Design and implement ML solutions aligned with GM’s autonomous driving objectives.

• Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling/selection, foundation modeling, to solve problems in object detection/tracking/classification, trajectory generation, and safe AI.

• Collaborate with cross-functional teams to deploy models and algorithms into onboard driving systems.

• Contribute to applied research efforts and remain current with advancements in ML frameworks and methods.

• Design and build efficient infrastructure, pipelines, and tooling to facilitate fast-pace model iterations.

• Drive technical execution from prototyping through production deployment, documenting learnings and best practices.

• Support and mentor engineers through technical collaboration and code reviews, fostering knowledge sharing and engineering excellence.

Your Skills & Abilities

• Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Machine Learning, or related field.

• Experience working with large-scale foundation models and alignment methods applied to real-world systems.

• Demonstrated ability to deliver applied ML solutions under real-world constraints and timelines.

• Proficiency in PyTorch and Python.

• Experience building and scaling model training pipelines enabling efficient iteration across teams.

• Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark.

• Strong communication skills enabling effective collaboration across engineering teams.

• Experience deploying ML models into production environments and understanding end-to-end deployment workflows.

• Experience in robotics or autonomous driving systems preferred.

Remote:

This role is based remotely but if you live within a 50-mile radius of Austin, Detroit, Warren,Milford or Mountain View, you are expected to report to that location three times perweek, at minimum.

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 represent for positions located outside of the California Bay Area.

• The salary range for this role is $218,800.00 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:

• 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 forrelocationbenefits.

Company Vehicle: 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.

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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.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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