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, and Robotics.
This is a summer 2025 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.
Our Computer Vision team is looking for Research Interns with experience in areas such as Generalizable Representation Learning, Video Understanding, Spatio-Temporal World Models, Unsupervised Object Discovery, Differentiable Rendering, Neural Implicit Representations, Generative Models and Self-Supervised Learning. We are aiming to push the boundaries of scene reconstruction methods to enable the safe and effective usage of large robotic fleets, simulation, and prior knowledge (geometry, physics shown experience, behavioral science), not only for automation but also for human augmentation, working towards Principle-Centric Artificial Intelligence (AI) for Embodied Foundation Models, in the context of Large Behavior Models (LBMs).
As a Research Intern, you will work with a multidisciplinary team proposing, conducting, and transferring cutting-edge research in Machine Learning. You will use large amounts of sensory data and simulation to solve open problems, publish at top academic venues, and test your ideas in the real world (including our robots of course!). You will also work closely with other teams at TRI to transfer and ship our most successful algorithms and models towards world-scale long-term autonomy and advanced assistance systems. Responsibilities and required qualifications are as follows.

Responsibilities

• Conduct high-reaching research in Machine Learning that solves open problems of high practical value and validate it in real-world benchmarks and systems.
• Push the boundaries of knowledge and the state of the art in ML areas including simulation, perception, prediction, and planning for autonomous driving and robotics.
• Partner with a multidisciplinary team including other research scientists and engineers across the ML team, TRI, Toyota, and our university partners.
• Stay up to date on the state-of-the-art in Machine Learning ideas and software.
• Present results in verbal and written communications, internally, at top international venues, and via open source contributions to the community.
• Participate in collaborations with our external research partners (e.g., Stanford, Berkeley, MIT, CMU, UMich).

Qualifications

• Currently pursuing a Ph.D. in Machine Learning, Robotics, Computer Vision, or related fields.
• Experienced in at least one key ML area among Computer Vision, ML theory, AI ethics, or related.
• At least one publication at high-impact conferences/journals (CVPR, ICLR, NeurIPS, CoRL, ICML, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.) on the aforementioned topics or other evidence of pioneering research work (e.g., via open source contributions).
• Some experience in scientific python, Unix, and a common DL framework (preferably PyTorch).
• You can work in collaboration with other researchers and engineers to invent and develop interesting research ideas.
• You are passionate about large scale challenges in ML grounded in physical systems, especially in the space of robotics. 
• You are a reliable team-player. You like to think big and have depth. You care about openness and delivering with integrity.

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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Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.