Robotics Machine Learning Research Scientist - Vision Language Action Foundation Models
Toyota Research InstituteLos Altos, California
Full Time
Posted December 3, 2025
$176k - $264k
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Job Description
The position involves conducting research in robotics and machine learning to develop general-purpose robots capable of performing dexterous tasks, utilizing large-scale models, multi-modal sensing, and reinforcement learning, with opportunities for experimentation, collaboration, and publication.
Key Responsibilities
- Develop and experiment with algorithms for robust policy learning using multiple sensing modalities such as proprioception, images, 3D representations, force, and tactile sensing.
- Scale machine learning approaches to large models trained on diverse datasets including web-scale text, images, and videos.
- Utilize test-time computation to enhance embodied robot applications.
- Improve learned policies efficiently and rapidly.
- Advance continual learning and adaptation techniques for robotics.
- Create multi-modal reasoning models and structured hierarchical reasoning systems.
- Implement reinforcement learning with language-based action models.
- Leverage history and memory to develop policies for long-context tasks.
- Enhance robustness and few-shot generalization using sub-optimal and self-play data.
- Design interactive agents capable of reducing ambiguity and seeking clarification during embodied tasks.
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 with 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 experience in Computer Science, Robotics, Electrical Engineering, or related fields.
- Experience in working with both simulated and real physical robots to run experiments.
- Ability to collaborate in code infrastructure development and participate in publishing work to peer-reviewed venues and open-sourcing code.
Benefits & Perks
Salary range between 176,000 and 264,000 USD per year (California-based roles)
Work with both simulated and real physical robots
Collaborate in code infrastructure and team members
Participate in publishing work to peer-reviewed venues
Open-source code contributions
Medical, dental, and 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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