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AI​/ML Engineer - Embodied AI

Job in Mountain View, Santa Clara County, California, 94039, USA
Listing for: generalmotors
Full Time position
Listed on 2026-10-08
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 219000 - 335000 USD Yearly USD 219000.00 335000.00 YEAR
Job Description & How to Apply Below
Position: Staff AI / ML Engineer - Embodied AI
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’returning today’sim possible 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 make driving 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 Num Py, 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 $ to $. 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.

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