Machine Learning Intern - Vision-Language-Action Pretraining

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 Fall 2025/Winter 2026 paid 12-week internship opportunity in Los Altos, HQ. Please note that this internship will be an in-office hybrid role.

The Mission

Make general-purpose robots a reality.

The Challenge

We envision a future where robots assist with household chores and cooking, aid the elderly in maintaining their independence, and enable people to spend more time on the activities they enjoy most. To achieve this, robots need to be able to operate reliably in messy, unstructured environments. Our mission is to answer the question “What will it take to create truly general-purpose robots that can accomplish a wide variety of tasks in settings like human homes with minimal human supervision?”. We believe that the answer lies in using large-scale datasets of physical interaction from a variety of sources and building on the latest advances in machine learning to learn general purpose robot behaviors from this data.

The Team

Our goal is to revolutionize the field of robotic manipulation, enabling long-horizon dexterous behaviors to be efficiently taught, learned, and improved over time in diverse, real world environments.

Within this broader mission, the Pretraining team focuses on building foundation models that can effectively bridge visual, language, and robotic domains. We combine large-scale model training with empirical validation in simulation and on physical robots, emphasizing both fundamental research advances and practical capabilities. Our work spans computer vision, multi-modal learning, and robotic control, with particular focus on scaling up model architectures, training data (action-free and data containing robot actions), and training approaches that generalize effectively to physical manipulation tasks.

The Internship

As a Research Scientist Intern, you will conduct research in robot foundation model pretraining alongside our core technical team. You'll work on developing and implementing large-scale multi-modal models that bridge visual, language, and robotic domains and validate them on our simulated and physical robot fleet.

For this internship specifically, the project will focus on pre-training autoregressive Vision-Language-Action (VLA) models, building on recent advances such as MolmoAct, with the goal of grounding multimodal reasoning in action spaces for robotics. In addition to large-scale autoregressive modeling, the work will involve co-training across multiple modalities -- including text, vision, depth, and action trajectories -- to enable richer representations and more robust cross-modal alignment. Explorations in this area will primarily focus on the data space (filtering web data, training on images and videos, etc.) while also leaving room for experimenting with novel architectural choices. The ideal candidate would preferably have some background in LLM/VLM training, as well as evaluating on robot simulation or real-world tasks.

• Advance the state of the art in training large-scale robot foundation models, and validate the impact of that research on real-world benchmarks and robots.
• Work as part of a dynamic, closely-knit research team.
• Implement high-performance machine-learning pipelines and optimize data and learning stacks for scalability, efficiency, and performance.
• Present results in verbal and written communications at international conferences, internally, and via open-source contributions to the community.
• Collaborate with internal research scientists, our engineering team, and our partner labs at top academic research universities including MIT, Stanford, Berkeley, CMU, Columbia, and Princeton to drive pioneering research at scale.

• Currently pursuing a Ph.D. in Machine Learning, Robotics, or related fields.
• Publications at high-impact conferences/journals (e.g., NeurIPS, ICML, ICLR, RSS, CoRL, CVPR, ACL, etc.) on some of the aforementioned topics.
• Passionate about large scale challenges in ML grounded in physical systems, especially in the space of robotics.
• Proficiency with one or more coding languages and systems, preferably Python, Unix, and a Deep Learning framework (e.g., PyTorch).
• Ability to work in collaboration with other researchers and engineers to invent and develop interesting research ideas.
• Experience training large-scale foundation models (LLMs, VLMs, diffusion models, etc) is desirable.
• Familiarity with robots and the challenges inherent in conducting research on physical hardware platforms is desirable.

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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