大语言模型后训练/Agentic算法工程师
Tasks
- Build LLM agent systems
- Build training and interaction environments
- Conduct error analysis and optimization
- Deploy agent capabilities in vehicle products
- Design reward modeling and preference learning
- Develop agent RL training pipelines
- Implement tool calling and multi tool reasoning
- Improve model reliability using real data
- Optimize LLM post training
- Run offline evaluation and online analysis
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic RL | DAPO | Distributed Training | Evaluation | Function Calling | GRPO | JSON | Java | Long Horizon Planning | Machine Learning | Memory | Multi-turn dialogue | Multimodal | NLP | On Policy | On policy Distillation | PPO | Planning | Policy Distillation | Preference Learning | Python | RLHF | RLVR | React | Reflection | Reinforcement Learning | Reward Modeling | Sparse Reward | Tool-Calling | TypeScript | Virtual Environment
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
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