At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.
This is a paid 12-week internship opportunity and is a hybrid, in-office role.
Here’s a glimpse into the Internship experience from some of our TRI interns!
The Team
Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from optimization, machine learning, and computer vision. We are pursuing a cooperative approach to high-performance driving by developing predictive models and control frameworks for extreme vehicle maneuvering that match or exceed the skills of expert drivers. We envision a world where these tools allow each vehicle to support its driver, creating a safe and enjoyable experience for all.
The Internship
We are looking for a research intern to develop new optimization, embodied reasoning, control, modeling, and/or perception methodologies for high-performance driving. This is an opportunity to apply your knowledge to novel problems and develop impactful research. This paid, 12-week, Summer 2026 internship is a hybrid in-office role in our headquarters in Los Altos, CA, and will involve experiments with high-performance vehicles on a closed racetrack.
Responsibilities
Develop new optimization, modeling, embodied reasoning, or/and perception algorithms.
Implement, deploy, and evaluate models and algorithms on high-performance cars.
Present results in verbal and written communications at international conferences and internally.
Qualifications
Ph.D. candidate working in: robotics, (differentiable) optimization, machine learning, control, Bayesian modeling, computer vision, embodied reasoning, or related fields.
Proficiency in at least one of the following: Python, C++, ROS(2), Pytorch, JAX.
Experience in deploying algorithms on real-world platforms.
Excellent collaboration and communication skills.
Strong interest in pushing the limits of vehicle autonomy and embodied AI.
