Lead Data Scientist
Tasks
- Debug training instabilities and policy collapse
- Design reinforcement learning agents for gaming domain
- Develop reward functions and learning strategies
- Document training pipelines and evaluation results
- Evaluate agents using success stability sample efficiency convergence
- Generalize reinforcement learning solutions across game engines
- Incorporate state event and perception signals into observation spaces
- Integrate reinforcement learning gameplay agents into games
- Optimize agent performance with hyperparameter tuning
- Refine model architecture and reward shaping
- Research and prototype reinforcement learning agents
Perks/Benefits
Skills/Tech-stack
Actor-critic | C++ | Experiment tracking | GRPC | Hyperparameter Tuning | Imitation Learning | Multi-Agent | Multi-Agent Reinforcement Learning | Offline Reinforcement Learning | OpenAI Gym | Policy Gradient | PyTorch | Python | Q-learning | REST | RabbitMQ | Reinforcement Learning | Reproducibility | Reward shaping | Rust | Self-play | Simulation | TensorFlow | Unity | Unreal Engine
Education
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