Staff AI/ML Engineer — Embodied AI Data Foundations

General Motors; Sunnyvale (CA); Hybrid; USD 189,000 - 300,000; Full time

Benefits offered by this job

Health benefits

GM vehicle discounts

401(k) plan

Job summary

General Motors in Sunnyvale, CA is seeking a Staff AI/ML Engineer to advance data-driven autonomous driving solutions. You will design scalable data curation and model training processes, leveraging real and synthetic datasets to improve safety and performance across diverse scenarios.

You will collaborate with AI/ML engineers, data scientists, and product teams, translating research into onboard and offboard ML solutions while mentoring peers and driving best practices in the autonomy stack.

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.
• Proven ability to deliver applied ML solutions under real-world constraints and timelines.
• Proficiency in PyTorch and Python.

Responsibilities

• Design ML solutions aligned with GM’s autonomous driving objectives.
• Apply unsupervised pre-training, imitation learning, reinforcement learning, and foundation modeling to solve problems in perception and control.
• Collaborate with cross-functional teams to deploy models into onboard driving systems.
• Develop and maintain model training pipelines enabling rapid iteration across teams.

Skills

PyTorch

Python

Data pipelines

Communication

ML in production

Education

CS/Robotics/ML degree

Tools

NumPy

Pandas

Apache Spark

Git

Job description

General Motors in Sunnyvale, CA is seeking a Staff AI/ML Engineer to advance data-driven autonomous driving solutions. You will design scalable data curation and model training processes, leveraging real and synthetic datasets to improve safety and performance across diverse scenarios.

You will collaborate with AI/ML engineers, data scientists, and product teams, translating research into onboard and offboard ML solutions while mentoring peers and driving best practices in the autonomy stack.