Staff AI/ML Engineer, Embodied Autonomy

Aimlroles; Mountain View, Northern (CA, KY); Hybrid; USD 219,000 - 335,000; Full time

Benefits offered by this job

Health benefits

Vehicle discounts

Relocation assistance

Job summary

General Motors is seeking a Staff AI/ML Engineer to develop and deploy ML solutions for autonomous driving. You will design advanced models, scale them for onboard use, and collaborate with cross-functional teams to push the autonomy stack forward.

You will mentor engineers, translate research into production-ready workflows, and stay current with the latest ML advances to improve system performance and safety across real-world driving scenarios.

Qualifications

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

Responsibilities

• Design and implement ML solutions aligned with GM’s autonomous driving objectives.
• Apply advanced ML techniques to object detection/tracking/classification, trajectory generation, and safe AI.
• Collaborate with cross-functional teams to deploy models into onboard driving systems.
• Contribute to applied research and stay current with ML framework advancements.
• Build efficient infrastructure, pipelines, and tooling for rapid model iterations.
• Drive technical execution from prototyping to production deployment with documentation.
• Mentor engineers through technical collaboration and code reviews.

Skills

PyTorch

Python

Foundation models

Data processing

Communication

Deployment

Education

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

Tools

NumPy

Pandas

Apache Spark

Job description

General Motors is seeking a Staff AI/ML Engineer to develop and deploy ML solutions for autonomous driving. You will design advanced models, scale them for onboard use, and collaborate with cross-functional teams to push the autonomy stack forward.

You will mentor engineers, translate research into production-ready workflows, and stay current with the latest ML advances to improve system performance and safety across real-world driving scenarios.