大模型算法工程师（开放域对话）
Tasks
- Accelerate inference with vLLM
- Address tool use hallucinations
- Apply DPO
- Apply GRPO
- Apply PPO
- Build end to end dialogue dataset
- Clean and deduplicate raw corpus
- Create evaluation set for complex interaction scenarios
- Develop LLM algorithms for open domain dialogue
- Evaluate with offline benchmarking
- Fine tune base model with SFT
- Implement dialogue state tracking optimization
- Improve multi turn dialogue decision success
- Optimize intent recognition recommendations and task success metrics
- Optimize models with RLHF and RLAIF
- Perform prompt engineering
- Run online A B testing
- Support model quantization and distillation
- Train reward model dataset for reinforcement learning
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | B testing | DPO | Data cleaning | Dataset Construction | Deduplication | DeepSpeed | Dialogue State Tracking | Distributed Training | Fine Tuning | Function Calling | GRPO | LLM | Language Models | Large Language Models | Model Distillation | Model Quantization | Offline evaluation | OpenRLHF | PPO | Prompt engineering | Python | RLAIF | RLHF | React | Reinforcement Learning | Reward Model | Reward Modeling | SFT | State tracking | Supervised Fine Tuning | Thought Intermediate Result | Tool use | VLLM
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Regions
Countries
States
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