强化学习算法工程师
Tasks
- Build agent simulation and replay environments for offline evaluation
- Build training and evaluation datasets from logs and feedback
- Collaborate with cross functional teams on data and feedback loops
- Design agent evaluation metrics and benchmarking system
- Design rewards and automated scoring mechanisms
- Develop reinforcement learning algorithms for robotic agents
- Optimize agent behavior policies and tool calling strategies
- Prototype advanced agent learning methods and enable business deployment
- Research offline reinforcement learning and preference learning
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | B testing | Data pipeline | Deep learning | Experiment design | Imitation Learning | JAX | LLM | LLM Agent | LLM Judge | Multi-turn dialogue | Offline Reinforcement Learning | Preference Learning | Prompt engineering | PyTorch | Python | RAG | Reinforcement Learning | Reward Modeling | TensorFlow | Tool-Calling | Workflow
Education
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