Machine Learning Research Scientist - Robotics, Trustworthy Learning under Uncertainty (TLU)
Tasks
- Build active learning and continual learning methods
- Conduct research on reliable robust adaptive deployment of machine learning models for robot manipulation
- Contribute open source software to the research community
- Develop large behavior models for robotics
- Develop rigorous policy evaluation methods
- Implement failure detection and mitigation approaches
- Present research results at conferences and in publications
Perks/Benefits
- 401k
- Annual cash bonus
- Dental insurance
- Medical insurance
- Paid time off
- Parental leave
- Vision insurance
Skills/Tech-stack
Active Learning | Cloud Computing | Continual Learning | Deep learning | Failure Detection | Foundation Models | Generative Modeling | Imitation Learning | Machine Learning | Multi-Modal | Multi-modal foundation models | Out-of-distribution Detection | Planning and control | Policy Evaluation | PyTorch | Python | Reinforcement Learning | Robotics | Safety-Aware Machine Learning | Uncertainty Estimation | Unix
Education
Regions
Countries
States
Cities
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