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Applied Reinforcement Learning Engineer

Remote Work( USA), United States R

USD 150K-300K Mid-level Full Time

@ C...
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Found 23h ago
Tasks
Perks/Benefits
Skills/Tech-stack

A2C | A3C | Actor-critic | Agent systems | BCQ | Behavioral cloning | CQL | DPO | Deep Q-Network | Dense Rewards | Direct Preference Optimization | Distributed Training | Domain Randomization | Double Deep Q Network | Dreamer | Dueling Deep Q Network | Eligibility Traces | GAIL | GRPO | Gated Loop | Gymnasium | Hierarchical reinforcement learning | Human Feedback | IQL | Intrinsic Motivation | JAX | KTO | Learning from Human Feedback | MDP | Markov Decision Process | Model Training | MuZero | Multi-Agent | Multi-Agent Systems | Offline Reinforcement Learning | OpenAI Gym | Options Framework | PPO | Policy Gradient | Policy Optimization | Potential Based Reward Shaping | Preference Learning | Preference optimization | Proximal Policy Optimization | PyTorch | Python | Q-learning | REINFORCE | RLOO | Reinforcement Learning | Reinforcement Learning from Human Feedback | Reward Model | Reward engineering | Reward model training | Reward shaping | Rllib | SAC | Sim-to-Real | Sim-to-Real Transfer | Simulation-based learning | Sparse Rewards | Stable Baselines | TD learning | TRPO | Temporal Difference | TensorFlow | World Models

Education

Master of Science | PhD

Roles

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

Regions

North America

Countries

United States

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