大模型算法工程师（开放域对话）
Tasks
- Accelerate inference with quantization and distillation
- Build end to end dialogue datasets
- Clean and deduplicate raw corpus
- Deploy low latency model in cloud and edge
- Develop LLM algorithms for open domain dialogue
- Evaluate offline and run A B testing
- Improve intent recognition and personalization
- Improve multi turn dialogue planning and decision making
- Optimize models with RLHF
- Optimize prompts with prompt engineering
- Reduce tool use hallucinations
- Run SFT for base models
- Track multi turn dialogue state
- Train reward model datasets for reinforcement learning
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AI Feedback | B testing | Dataset cleaning | Deduplication | DeepSpeed | Dialogue State Tracking | Distributed Training | Function Calling | GRPO | Human Feedback | Inference acceleration | Knowledge Distillation | Language Models | Large Language Models | Learning from Human Feedback | Offline evaluation | OpenRLHF | PPO | Prompt engineering | Python | Quantization | React | Reinforcement Learning | Reinforcement Learning from AI Feedback | Reinforcement Learning from Human Feedback | Reward Modeling | SFT | State tracking | Thought Intermediate Result | Tool use | User Simulator | VLLM | World Model
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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