Staff ML Engineer, Embodied AI Foundations (Remote)

General Motors Ventures; United States; Hybrid; Confidential; Full time

Benefits offered by this job

Health benefits

Retirement savings plan

HSA/FSAs

GM vehicle discounts

Job summary

General Motors is seeking a Staff AI/ML Engineer to advance autonomous driving through advanced data curation and model training using real and synthetic datasets. You will design scalable pipelines, collaborate with cross-functional teams, and mentor engineers to drive safe and reliable vehicle behavior across diverse scenarios.

You will work with foundation models, PyTorch, Python, and large-scale data to deliver production-ready ML solutions and continuously improve the autonomy stack.

Qualifications

• Advanced degree in CS, robotics, or ML or equivalent experience.
• Experience with large-scale foundation models and alignment methods.
• Proven ability to deliver ML solutions in real-world timelines.

Responsibilities

• Design and implement ML solutions aligned with GM's autonomous driving objectives.
• Apply unsupervised pre-training, imitation learning, reinforcement learning, and foundation modeling.
• Collaborate with cross-functional teams to deploy models into onboard systems.
• Contribute to research and stay current with ML frameworks and methods.
• Build infrastructure, pipelines, and tooling for fast model iteration.
• Drive execution from prototyping to production and document learnings.
• Mentor engineers and participate in code reviews to share knowledge.

Skills

Foundation models

PyTorch

Python

Data pipelines

Large-scale data

Communication

Deployment workflows

Autonomous driving

Education

Bachelor's/Master's/PhD in CS/Robotics/ML

Tools

NumPy/Pandas

Apache Spark

Python ecosystem

Job description

General Motors is seeking a Staff AI/ML Engineer to advance autonomous driving through advanced data curation and model training using real and synthetic datasets. You will design scalable pipelines, collaborate with cross-functional teams, and mentor engineers to drive safe and reliable vehicle behavior across diverse scenarios.

You will work with foundation models, PyTorch, Python, and large-scale data to deliver production-ready ML solutions and continuously improve the autonomy stack.