Applied Scientist - Reinforcement learning, OMHS SCS
North Reading, Massachusetts, USA
USD 142K-193K Entry-level Full Time
Tasks
- Build simulation environments
- Deploy control policies
- Design reinforcement learning agents
- Develop reinforcement learning solutions
- Implement reward models
- Integrate reinforcement learning into production control systems
- Optimize policies
- Train offline reinforcement learning models
- Transfer policies to real world
- Validate policies in simulation
Perks/Benefits
- 401k matching
- Dental insurance
- Employee assistance program mental health support
- Flexible spending accounts
- Health insurance
- Medical Advice Line
- Paid time off
- Parental leave
- Vision insurance
Skills/Tech-stack
Actor-critic | C++ | Contextual Bandits | Decision Making | Deep reinforcement learning | Isaac-Gym | Mujoco | Multi-Agent | Multi-Agent Reinforcement Learning | Offline Reinforcement Learning | Omniverse | OpenAI Gymnasium | Policy Gradient | Policy Optimization | PyTorch | Python | Ray RLlib | Reinforcement Learning | Reward Modeling | Sequential decision making | Sim-to-Real | Simulation | Stable-Baselines3 | TensorFlow
Education
Roles
Regions
Countries
States
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