Senior AI Research Scientist (Model-based RL)
Tasks
- Apply constrained control methods
- Build world models
- Collaborate with engineers and partners
- Define new research directions
- Design model based reinforcement learning agents
- Develop Bayesian reinforcement learning approaches
- Develop learned dynamics models
- Document research findings
- Implement planning based controllers
- Lead research rollout
- Mentor research engineers
- Perform scenario planning
- Present technical results
- Research safe reinforcement learning methods
- Translate research into production solutions
Perks/Benefits
- Company provided MacBook
- Dental insurance
- Equity participation
- Flexible stipends
- Fully remote
- Medical insurance
- Paid parental leave
- Remote-first culture
- Training programs
- Unlimited paid time off
- Vision insurance
Skills/Tech-stack
Bayesian Reinforcement Learning | Cloud Computing | Constrained Control | Control Theory | Deep learning | Distributed Computing | Docker | GCP | Kubernetes | Learned Dynamics | MPPI | Model Free Reinforcement Learning | Model-Predictive Control | Model-based reinforcement learning | Planning Algorithms | Predictive control | PyTorch | Python | Ray | Reinforcement Learning | Safe Reinforcement Learning | Scenario Planning | SciPy | Simulation to Real | Simulation-to-Real transfer | World Models
Education
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