Robotics Machine Learning Research Scientist - Large Behavior Models
Toyota Research InstituteLos Altos, California
Full Time
Posted December 3, 2025
$176k - $264k
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Job Description
A research scientist position focused on developing large-scale machine learning models and algorithms for dexterous robot manipulation, utilizing diverse data sources and simulation to advance general-purpose robotics in unstructured environments.
Key Responsibilities
- Develop and research algorithms for learning robust policies using multiple sensing modalities such as proprioception, images, 3D representations, force, and tactile sensing.
- Scale learning approaches to large-scale models trained on diverse data sources including web-scale text, images, and videos.
- Leverage test-time computation to enhance embodied robot applications.
- Improve learned policies efficiently and rapidly.
- Advance continual learning and adaptation techniques for robotics.
- Design and develop multi-modal reasoning models and structured hierarchical reasoning using learned models.
- Implement reinforcement learning with language action models and utilize history and memory for long-context policy learning.
- Enhance robustness and few-shot generalization by incorporating sub-optimal and self-play data.
- Create interactive agents capable of reducing embodied and instructional ambiguity, seeking help and clarification when needed.
- Collaborate on code infrastructure, run experiments with simulated and real robots, and contribute to research publications and open-source projects.
Requirements
- A research scientist who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data.
- Experience in developing data-efficient and general algorithms for learning robust policies using multiple sensing modalities including proprioception, images, 3D representations, force, and dense tactile sensing.
- Experience in scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video.
- Ability to leverage test time computation for embodied applications.
- Ability to quickly and efficiently improve learned policies.
- Experience or knowledge in Continual Learning and Adaptation.
- Experience in developing Multi-Modal Reasoning Models.
- Experience in structured hierarchical reasoning using learned models.
- Experience in Reinforcement Learning with Language Action Models.
- Ability to leverage history and memory for learning policies for long context tasks.
- Experience in improving robustness and few-shot generalization by using sub-optimal and self-play data.
- Experience in developing interactive agents that can reduce embodied and instructional ambiguity and can seek help and clarification.
- A minimum of a Ph.D. or equivalent in Computer Science, Robotics, Machine Learning, or a related field.
- Proficiency in collaborating in code infrastructure, working with team members, and running experiments with both simulated and real physical robots.
Benefits & Perks
Salary range between 176,000 and 264,000 per year (California-based roles)
Medical insurance
Dental insurance
Vision insurance
401(k) eligibility
Paid time off including vacation, sick leave, and parental leave
Annual cash bonus
Ready to Apply?
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