Human Interactive Driving Research Intern, Uncertainty – Aware Optimization and Control

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 in Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.
This is a summer 2025 paid 12-week internship opportunity with the HID team in the EPIC (Extreme Performance Intelligent Control ) department at TRI. Please note that this internship will be a hybrid in-office role based in Los Altos, CA, and will involve experiments with high-performance vehicles on a closed racetrack.
The Mission
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 in Human Interactive Driving, Human-Centered AI, Energy and Materials, Large Behavior Models, and Robotics.
The Team
Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from optimal control, 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
In this project, we are interested in developing new optimization-based control methodologies that reason about uncertainty for high-performance driving. This is an opportunity to apply your knowledge to novel problems and develop impactful research. This internship will involve experiments with high-performance vehicles on a closed racetrack.

Responsibilities

• Design novel optimization-based control algorithms for use in a vehicle autonomy stack
• Implement, deploy, and evaluate models and algorithms on high-performance cars
• Present results in verbal and written communications at international conferences and internally

Qualifications

• Currently enrolled in a Ph.D. or equivalent experience working on related fields: optimization, control, and machine learning
• Proficiency in at least one of the following: Python, C++, ROS(2), Pytorch, JAX
• Experience in deploying algorithms on real-world platforms
• Strong collaboration, communication, and interpersonal skills
• Strong curiosity and interest about pushing the limits of vehicle autonomy

Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.
The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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