Large Behavior Models (LBM) Research Scientist Intern, Policy Learning
Los Altos, CA
Internship Entry-level / Junior USD 90K - 130K
Toyota Research Institute
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.
The MissionMake general-purpose robots a reality.
The ChallengeWe 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 TeamOur 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 InternshipAs 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.
Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
This is a Summer 2025 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.
The MissionMake general-purpose robots a reality.
The ChallengeWe 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 TeamOur 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 InternshipAs 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.
Responsibilities
- 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.
Qualifications
- Currently pursuing a Ph.D. in Machine Learning, Robotics, or related fields.
- Publications at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, UAI, ICLR, RSS, ICRA, IROS, 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 (VLMs, text-to-video models, etc) is desirable.
- Familiarity with robots and the challenges inherent in conducting research on physical hardware platforms is desirable.
Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
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Categories:
Data Science Jobs
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Tags: Architecture Computer Vision Deep Learning Engineering ICLR ICML Machine Learning Model training NeurIPS Open Source Pipelines Privacy Python PyTorch Research Robotics
Perks/benefits: Career development Conferences Team events
Region:
North America
Country:
United States
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