Automated Driving Advanced Development Intern, Machine Learning Research

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.

The Team

The Automated Driving Advanced Development division bridges TRI research and Toyota products. In partnership with Woven by Toyota, the team is researching and developing an end-to-end learned driving stack that maps sensor inputs directly to planned trajectories.

The Internship

We are seeking a research intern to investigate foundation models and generative AI for autonomous driving. You will work with TRI researchers to define and pursue a research question aligned with your interests and the team’s ongoing work. Potential directions include multimodal reasoning and agents; generative models for action, world modeling, and simulation; and learning and evaluation through interaction. These directions are flexible, and we welcome ideas that connect them or bring a complementary perspective.

You’ll lead an independent research project shaped around your interests and the team’s ongoing work. Potential directions include language and vision-language models, coding agents, generative driving policies, world models and simulation, and learning from closed-loop feedback. You’ll work with Toyota driving data and closed-loop simulation infrastructure, with the goal of producing work suitable for a research paper submission. The internship offers an opportunity to own a focused research contribution while collaborating on broader questions in physical intelligence. Outcomes may include research prototypes, technical reports, and contributions to publications. 

The Opportunity

As a research intern on AD2, you will own a standalone research project in sim-to-sim and sim-to-real domain mapping, with the opportunity to:

• Drive your own research: Shape the approach, run experiments, and analyze results, with the independence to set your own direction.

• Publish your findings: The project is designed to produce results suitable for publication.

• Shape a real autonomy model: The tools and insights you create will help the team improve our autonomy models, with the potential to influence the autonomy stack eventually deployed in Toyota vehicles.

• Collaborate with experienced researchers: Work closely with a small team of industry-leading researchers with deep experience in robotics and autonomous driving.

• Work at scale: Use the same large-scale Toyota driving data, base models, and simulation infrastructure the team uses every day.

You can learn more about our work on the Automated Driving Advanced Development team page .