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 Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics.

This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.

The Team

Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from machine learning, optimization, and control theory. 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 perception, modeling, and/or control methodologies for high-performance driving that infer and reason about uncertainty. 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 novel perception algorithms for high-performance driving.
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 on related fields: robot perception, computer vision, robot learning, deep learning, or related fields.
Proficiency in at least one of the following: Python, C++, ROS(2), Pytorch, CUDA, JAX.
Familiarity in one of the following areas: semantic mapping, SLAM, and foundation models.
Experience in deploying algorithms on real-world platforms.
Excellent collaboration and communication skills.
Strong interest in pushing the limits of robot autonomy.
Strong publication records in top conferences and journals, including RSS, CVPR, ECCV, ICCV, ICRA, RA-L, NeurIPS, ICLR, etc.

Bonus Qualifications

Publications related to semantic mapping, neural distance fields, Gaussian Splatting.
Publications related to SLAM, Lidar/Visual Odometry, and Structure from Motion.
Publications related to foundational models.

Please add a link to Google Scholar to include a full list of publications when submitting your CV for 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. Base pay offered may vary depending on multiple individualized factors, including, but not limited to, business or organizational needs, 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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TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.

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Human Interactive Driving Intern

Localization and Mapping

Toyota Research Institute

Compensation Overview

Responsibilities

Qualifications

Bonus Qualifications