Human Interactive Driving Research Intern, Decision-Making for Driving at the Limits

Toyota Research Institute•Los Altos, CA

5d•Hybrid

About The Position

Toyota Research Institute (TRI) is seeking a research intern to develop optimization, embodied reasoning, control, modeling, and/or perception methodologies for high-performance driving. The intern will work with the Extreme Performance Intelligent Control team, which advances vehicle safety and performance using optimization, machine learning, and computer vision. The team develops predictive models and control frameworks for extreme vehicle maneuvering, aiming to match or exceed expert-driver capabilities and support safe, enjoyable driving. This is a paid, 12-week Summer 2026 internship. It is a hybrid, in-office role at TRI headquarters in Los Altos, California, and includes experiments with high-performance vehicles on a closed racetrack. The intern will implement, deploy, and evaluate algorithms on high-performance cars and communicate results internally and at international conferences.

Requirements

Be a Ph.D. candidate working in robotics, (differentiable) optimization, machine learning, control, Bayesian modeling, computer vision, embodied reasoning, or a related field.
Proficiency in at least one of Python, C++, ROS(2), PyTorch, or JAX.
Experience deploying algorithms on real-world platforms.
Excellent collaboration and communication skills.
Strong interest in pushing the limits of vehicle autonomy and embodied AI.

Nice To Haves

Include links to relevant open-source contributions or technical project write-ups with the application.

Responsibilities

Develop new optimization, modeling, embodied reasoning, and/or perception algorithms.
Implement, deploy, and evaluate models and algorithms on high-performance cars.
Present results verbally and in writing at international conferences and internally.