Llm算法实习生(具身大脑方向)
Tasks
- Apply SFT RL and RLHF workflows to interactive tasks
- Build long term real time interaction simulation tasks
- Conduct experiment analysis and internal technical discussions
- Create environment feedback reward signals and task verification
- Design multi step interactive task environments
- Track LLM agent embodied AI and agentic RL research progress
- Train agentic reinforcement learning using interaction trajectories
- Write technical reports and research summaries
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic RL | Data Annotation | Fine Tuning | Human Feedback | LLM Agent | Language Models | Large Language Models | Learning from Human Feedback | Machine Learning | Multi-step Planning | PyTorch | Reinforcement Learning | Reinforcement Learning from Human Feedback | Reward Design | Supervised Fine Tuning | Task planning | Tool use | Trajectory Data
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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