大模型算法工程师（开放域对话）
Tasks
- Accelerate model inference with quantization distillation and efficient frameworks
- Apply RLHF and RLAIF optimization
- Build end to end dialogue data pipelines
- Clean and deduplicate raw training data
- Collaborate on distributed training and deployment
- Develop LLM algorithms for open domain dialogue
- Improve multi turn dialogue decision making using agentic RL
- Mitigate hallucinations in agent tool use
- Optimize base model with SFT
- Optimize intent recognition and personalization performance
- Perform prompt engineering
- Run offline evaluations and online A B testing
- Track dialogue state using DST
- Train reward model datasets for reinforcement learning
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Agentic reinforcement learning | B testing | DeepSpeed | DisTaTch State Tracking DST | Distributed Training | Function Calling | Group Relative Policy Optimization | Group Relative Policy Optimization GRPO | Knowledge Distillation | LLM | Language Models | Large Language Models | Online Experimentation | OpenRLHF | Prompt engineering | Proximal Policy Optimization | Proximal Policy Optimization PPO | Python | Quantization | RLAIF | RLHF | React | Reinforcement Learning | Reward Modeling | Supervised Fine Tuning | Supervised Fine-Tuning (SFT) | Thought Intermediate Result | VLLM
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Regions
Countries
States
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