大语言模型后训练/Agentic算法工程师
Tasks
- Advance LLM post training
- Analyze real vehicle interaction errors
- Build agent harness and automated evaluation framework
- Build next generation LLM agent for intelligent cockpit
- Create world model and reward function
- Design tool system and user simulator
- Develop agentic RL algorithms
- Develop task assistant agents
- Implement multi tool calling
- Optimize multi turn reasoning decision making
- Optimize solutions with offline and online feedback
- Perform data mining and error attribution
- Reproduce and validate LLM post training methods
- Research and train vehicle dialogue systems
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic RL | DAPO | Distributed Training | Evaluation Frameworks | Function Calling | GRPO | Inference Serving | JSON | Java | Language Processing | Learning algorithms | Long Horizon Task Learning | Machine Learning | Memory | Model Training | Natural Language | Natural Language Processing | On Policy | On policy Distillation | OpenRLHF | PPO | PPO Reinforcement Learning | Planning | Policy Distillation | Preference Learning | Python | RLHF | RLVR | React | Reflection | Reinforcement Learning | Reinforcement learning algorithms | Reward Modeling | Sparse Reward | Sparse Reward Modeling | TRL | Tool Integrated Reasoning | Trajectory Optimization | TypeScript | VeRL
Education
Regions
Countries
States
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