Embodied AI Research Intern — Autonomous Driving (PhD)

General Motors; Sunnyvale (CA); Hybrid; USD 148,000 - 178,000; Full time

Benefits offered by this job

Paid U.S. GM holidays

GM Family First Vehicle Discount

Growth opportunities and mentorship

Job summary

General Motors is seeking an Embodied AI Research Intern in Sunnyvale, CA, to conduct applied research at the intersection of machine learning, robotics, and autonomous driving. You will work with senior researchers to develop hypotheses, run experiments, train models, and communicate results.

Focus areas include foundation models for autonomy, vision-language-action models, generative and world models, and planning/control learning.

Qualifications

• Pursuing or in process of obtaining a Ph.D. in ML/AI/CS/Robotics or related field.
• Strong understanding of modern ML/DL methods.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX).
• Demonstrated AI/ML research through coursework, projects, publications, or similar work.
• Ability to design experiments and interpret results.
• Strong communication and teamwork skills.
• Availability for full-time, 40 hours/week internship period.

Responsibilities

• Formulate research problems and develop prototypes for autonomous driving applications.
• Design and run experiments, ablation studies, and quantitative evaluations.
• Train and benchmark models using large-scale datasets and distributed compute.
• Analyze model behavior, failures, generalization, and tradeoffs.
• Collaborate with perception, planning, robotics, controls, and systems teams.
• Contribute to technical discussions, documentation, publications, or open-source work.

Skills

Python

ML/DL fundamentals

Analytical thinking

Team collaboration

Public speaking

Education

Ph.D. in ML/AI/CS/Robotics

Tools

PyTorch

TensorFlow

JAX

Job description

General Motors is seeking an Embodied AI Research Intern in Sunnyvale, CA, to conduct applied research at the intersection of machine learning, robotics, and autonomous driving. You will work with senior researchers to develop hypotheses, run experiments, train models, and communicate results.

Focus areas include foundation models for autonomy, vision-language-action models, generative and world models, and planning/control learning.