Llm算法实习生（具身大脑方向）
Tasks
- Build long term real time interaction task simulations
- Conduct experiments and analyze results
- Design reward signals and task verification mechanisms
- Prepare interaction trajectory datasets
- Track LLM agent embodied AI and agentic RL research progress
- Train agentic reinforcement learning with environment feedback
- Write technical reports and research summaries
Perks/Benefits
- N/A
Skills/Tech-stack
Embodied AI | Fine Tuning | Human Feedback | LLM Agents | Language Models | Large Language Models | Learning from Human Feedback | Long-term planning | Multi-turn dialogue | PyTorch | Reinforcement Learning | Reinforcement Learning from Human Feedback | Robotics | Simulation | Supervised Fine Tuning | Tool use
Education
N/A
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