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Applied Reinforcement Learning Engineer

Redmond, Washington, United States

USD 150K-160K Mid-level Full Time

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Found 2d ago
Tasks
Perks/Benefits
Skills/Tech-stack

A2C | A3C | Actor-critic | Agent systems | BCQ | Behavioral cloning | CQL | DPO | Deep Q-Network | Domain Randomization | Double Deep Q Network | Dreamer | Dueling Deep Q Network | Eligibility Traces | Entropy Regularization | GAIL | GRPO | Gymnasium | Hierarchical reinforcement learning | IQL | JAX | MDP | MuZero | Multi-Agent | Multi-Agent Systems | Multi-step reasoning | Offline RL | OpenAI Gym | Options Framework | PPO | Policy Gradient | PyTorch | Python | Q-learning | RLHF | RLOO | Reinforcement Learning | Reward Modeling | Reward engineering | Rllib | SAC | Simulation to Real | Stable Baselines | TD Lambda | TRPO | TensorFlow | Tool use | Trust Region | World Models

Education

Master of Science | PhD

Roles

Applied Reinforcement Learning Engineer | Engineer | Learning Engineer | Reinforcement Learning Engineer

Regions

North America

Countries

United States

States

Washington, US

Cities

Redmond, Washington, US

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