大语言模型后训练/Agentic算法工程师
Tasks
- Build LLM post training for vehicle intelligence
- Conduct multi turn dialogue system research
- Design tool user simulator and world model environments
- Develop agentic RL training pipelines
- Implement multi tool calling and function calling
- Optimize reward modeling and preference learning
- Perform error attribution and data driven improvement
- Set up automated evaluation and offline online analysis
Perks/Benefits
- N/A
Skills/Tech-stack
Distributed Training | Function Calling | GRPO | Human Feedback | JSON | Java | Language Processing | Large Language Model | Large Language Model Agents | Learning from Human Feedback | Machine Learning | Memory | Multi Tool Calling | Multi-turn dialogue | Natural Language | Natural Language Processing | On Policy | On policy Distillation | PPO | Planning | Policy Distillation | Preference Learning | Python | RLHF | React | Reflection | Reinforcement Learning | Reinforcement Learning from Human Feedback | Reinforcement Learning from Video Feedback | Reward Modeling | Tool Integrated Reasoning | Tool-Calling | TypeScript | Video Feedback
Education
Regions
Countries
States
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