大模型算法研究员
Tasks
- Analyze training curves and error cases
- Build agent memory and reflection
- Build training data pipeline
- Clean and analyze training data
- Collaborate with engineering and robotics teams
- Design task planning and environment interaction
- Develop LLM agent tool calling
- Develop large language model post training algorithms
- Develop model training and evaluation workflow
- Evaluate model behavior and training stability
- Implement continual learning
- Implement online distillation
- Research reinforcement learning
- Research supervision fine tuning
- Support system deployment
Perks/Benefits
- N/A
Skills/Tech-stack
AI Feedback | Autoregressive Generation | Data Quality | Data Sampling | Data cleaning | Data pipeline | Data quality analysis | Deep learning | Distributed Training | Environment interaction | Fine Tuning | GPU Memory Optimization | GPU memory | Human Feedback | Knowledge Distillation | Language Models | Large Language Models | Learning from Human Feedback | Machine Learning | Memory Optimization | Model Evaluation | Model Training | Model fusion | Online Distillation | Preference Learning | PyTorch | Python | Quality analysis | Reinforcement Learning | Reinforcement Learning from AI Feedback | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Task planning | Tool-Calling | Transformer
Education
N/A
Regions
Countries
States
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