Careers at Tri

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. The Learning From Videos (LFV) team develops world foundation models that leverage large-scale multi-modal data (RGB, depth, flow, semantics, actions, tactile, audio, etc.) from multiple domains to power downstream embodied AI tasks. Our topics of interest include Video Generation, World Models, 4D Reconstruction, Multi-Modal Models, Multi-View Geometry, Data Augmentation, and Video-Language-Action models, with a primary focus on embodied applications such as robotics and driving. We are making progress on some of the hardest scientific challenges around spatio-temporal reasoning, and how it can lead to the deployment of autonomous agents in real-world unstructured environments. Our team is looking for a Research Engineer to help develop and deploy our world foundation models (WFMs) toward their key milestones in the autonomous driving domain. As our WFMs scale in both capability and ambition, we need a strong engineer who can bridge the gap between research ideas and production-grade systems. This is not a traditional software engineering role; you will work directly alongside research scientists, understand the research deeply enough to make independent technical decisions, and play a key role in enabling the deployment of key research breakthroughs into close-to-production environments. As a Research Engineer, you will be responsible for supporting and optimizing large-scale distributed training of diffusion and transformer models; maintaining the infrastructure that ingests, unifies, and serves heterogeneous multi-modal datasets at scale; and developing tools and pipelines that accelerate the research-to-results cycle. You will work closely with researchers to prototype new ideas, run experiments, and help ship our most successful models toward real-world applications with real-world impact. This role requires close collaboration with multiple TRI divisions (Robotics, Automated Driving, Human-Interactive Driving, etc.) as well external Toyota and University partners, and the ability to reconcile and prioritize possibly competing requirements in a fast-paced combination of research and production environments.

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. The Automated Driving Advanced Development division at TRI will focus on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared commitment. This new division is leading a new cross-organizational project between TRI and Woven by Toyota to conduct research and develop a fully end-to-end learned driving stack. This cross-org collaborative project is harmonious with TRI’s robotics divisions' efforts in Diffusion Policy and Large Behavior Models. We are looking for a Senior Data Engineer to design and build the foundational data infrastructure and tools that power our autonomy research and development workflows. This includes large-scale ingestion pipelines, structured feature stores, labeling infrastructure, scene search and data discovery tools, and performance diagnostics for machine learning and simulation workflows.

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. The Team The Automated Driving Advance Development division at TRI focuses on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared commitment. The Automated Driving Advance Development team is leading a new cross-organizational project between TRI and Woven by Toyota to research and develop a fully end-to-end learned automated driving / ADAS stack. This cross-org collaborative project is synergistic with TRI’s robotics divisions' efforts in Diffusion Policy and Large Behavior Models (LBM). The Opportunity We are looking for a Senior Machine Learning Researcher to join us in developing a state-of-the-art, pixels-to-action, end-to-end system for automated driving. As an expert in machine learning, you will contribute to designing and developing innovative models for our autonomy stack and deploying them on vehicle platforms to solve daily driving tasks and handle long-tail scenarios. An ideal candidate has a strong track record of leading independent research efforts, preferably including mentoring and collaborating with less experienced students and researchers. You will help to drive our exploration into end-to-end learning approaches for automated driving, using large-scale sensor data directly for perception, planning, and prediction to overcome traditional "information bottlenecks." This includes expanding our successful Large Behavior Model (LBM) robotics efforts and Diffusion Policy (DP) research into the driving domain, designing scalable architectures, and integrating visual-language-action modalities. Beyond refining models for closed-loop driving on public roads and in simulation, you will also explore data quality filtering, transfer learning from diverse data sources, and edge deployment optimization. This work is part of Toyota’s global AI efforts to build a more coordinated global approach across Toyota entities.

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! Team We are a group of researchers building agentic AI systems for a diverse range of applications, including robotics, vehicle design, factory logistics, and numerical optimization. About the Internship A successful candidate would have a background in both agentic AI and one of the above applications. This is an opportunity to apply your knowledge to novel research questions and work towards a publication with professional researchers. The internship will be in our Cambridge office and includes competitive compensation befitting the challenging but fun nature of the research work at TRI.

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!

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!

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 Our Trustworthy Learning under Uncertainty (TLU) team in the Robotics division is looking for Research Interns for Summer 2027 in a variety of areas such as Policy Evaluation, Failure Detection and Mitigation, as well as (Inter)Active and Continual Learning in the context of World Foundation Models (WFM) for Robot Manipulation. Our topics of interest include but are not limited to: Multi-Modal Foundation Models, Generative Modeling, Imitation Learning, Reinforcement Learning, Planning & Control, Statistics, Uncertainty Estimation, Out-of-Distribution Detection, Safety-Aware & Robust ML, (Inter)Active Learning, and Online / Continual Learning. We are aiming to make progress on some of the hardest scientific challenges around the safe and effective usage and development of machine learning algorithms within Robotics. To this end, the research mission of the TLU team is to enable the robust and reliable deployment of embodied foundation models at scale in human environments, while allowing for efficient adaptation to novel settings. The Internship As a Research Intern, you will work with a multidisciplinary team proposing, conducting, and transferring pioneering research in Machine Learning for Robot Manipulation. You will use large amounts of sensory data and simulation to solve open problems, work towards publications at top academic venues, and test your ideas in the real world, including on our robots, of course!

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 The World Foundation Models (WFM) team in the Robotics division is looking for research interns for the summer of 2027 in a variety of areas such as Video Generation, World Modeling, World-Action Models, 4D Reconstruction, Learning from Egocentric Videos, Multi-Modal Foundation Models, Multi-View Geometry, and Data Augmentation, with a primary focus on on embodied applications. We are aiming to make progress on some of the hardest scientific challenges around the deployment of robots in unstructured environments, by leveraging data from different sources and modalities, and learning transferable priors grounded in physical properties found in the real-world. Our mission is to develop foundational models capable of understanding how the world works, and in doing so predict possible future states from available information and adapt to new environments and circumstances. The Internship As a Research Intern, you will work with a multidisciplinary team proposing, conducting, and transferring pioneering research on the intersection between Computer Vision and Robotics. You will use large amounts of data from different sources and modalities, and train large-scale foundation models aimed at solving open problems, work towards publications at top academic venues, and test your ideas in simulators as well as in the real world.

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 Our team in the Robotics division is developing pretrained generalist policies that can support a broad range of tasks, environments, and robotic systems. A central scientific challenge is determining how these broadly pretrained policies can be efficiently adapted to new target tasks while achieving the reliability, precision, and robustness required for real-world use. Pretraining can provide a policy with broad behavioral capabilities, but those capabilities may not immediately translate into dependable performance in a specific deployment setting. Effective post-training methods are therefore essential for converting general capabilities into policies that can adapt quickly, learn from limited additional data or interaction, and perform consistently on demanding downstream tasks. The Opportunity Our research interests include reinforcement learning, imitation learning, human-in-the-loop learning, simulation, world models, policy distillation, and large-scale robot learning. We aim to advance the scientific foundations of policy adaptation while developing methods that may ultimately be evaluated or deployed within internal research projects involving real-world industrial tasks. Potential research directions include, but are not limited to: Offline-to-online reinforcement learning DAgger, imitation learning, and human-in-the-loop policy improvement Sim-to-real policy distillation and adaptation Policy improvement, planning, or data generation using world models Data-efficient adaptation to new tasks and environments