大模型算法工程师（开放域对话）
Tasks
- Apply DPO
- Apply GRPO
- Apply PPO
- Build end to end dialogue data pipeline
- Clean and deduplicate raw corpus
- Deploy low latency inference on edge or cloud
- Develop LLM algorithms for open domain dialogue
- Evaluate dialogue using offline evaluation
- Implement multi turn state tracking DST
- Improve intent recognition and personalization
- Improve multi turn dialogue decision making using agentic RL
- Optimize base model with SFT
- Optimize models with RLHF
- Perform prompt engineering
- Reduce hallucinations in tool use
- Run offline evaluation and online A B testing
- Support model quantization distillation and inference acceleration
- Train reward model for reinforcement learning
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Agentic RL | B testing | DPO | Data Deduplication | Data cleaning | DeepSpeed | Distributed Training | Fine Tuning | Function Calling | GRPO | Inference Optimization | Knowledge Distillation | Language Models | Large Language Models | Model Quantization | OpenRLHF | Policy Optimization | Prompt engineering | Proximal Policy Optimization | Python | RLAIF | RLHF | React | Reinforcement Learning | Reward Modeling | Supervised Fine Tuning | TRL | Thought Intermediate Result | VLLM | VeRL
Education
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