Human Interactive Driving Research Intern, Perception for Driving at the Limits

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 develop 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 accelerated perception and filtering frameworks for on-board extreme vehicle maneuvering that match or exceed the skills of expert drivers. We envision a world where these vehicles enable their drivers, creating a safe and enjoyable experience for all. The Opportunity We are looking for a research intern to develop new perception, embodied reasoning, modeling, and/or control methodologies for high-performance driving. This is an opportunity to apply your knowledge to novel problems and develop impactful research that is validated in hardware. This paid, 12-week, Summer 2027 internship is a hybrid in-office role at our headquarters in Los Altos, CA, and will involve experiments with high-performance vehicles on a closed racetrack. Responsibilities • Develop new perception, modeling, embodied reasoning, and/or control algorithms. • Implement, deploy, and evaluate models and algorithms on high-performance cars. • Present results in verbal and written form internally and at international conferences. Qualifications • Ph.D. candidate working in: computer vision, machine learning, robotics, embodied reasoning, or related fields. • Proficiency in at least one of the following: Python, C++, ROS(2), PyTorch, JAX. • Experience with geometric foundation models, LiDAR/visual inertial odometry stacks, and/or Bayesian filtering methods. • 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.