大语言模型后训练算法工程师
Tasks
- Collaborate with data and product teams
- Collect application feedback
- Define delivery standards
- Deploy LLM inference services
- Deploy LLM tuning frameworks
- Design LLM reinforcement learning experiments
- Design LLM supervised fine tuning experiments
- Ensure model accuracy safety and consistency
- Improve training framework stability
- Optimize LLM inference performance
- Optimize cloud training pipeline efficiency
- Optimize model evaluation system
- Optimize multi machine communication
- Optimize resource scheduling
Perks/Benefits
- N/A
Skills/Tech-stack
Distributed Training | Docker | Fine Tuning | Human Feedback | Kubernetes | LLM Inference | Language Model | Large Language Model | Learning from Human Feedback | Machine communication | Model Evaluation | Multi Machine Communication | PyTorch | Python | Ray Serve | Reinforcement Learning | Reinforcement Learning from Human Feedback | Resource scheduling | SGLang | Supervised Fine Tuning | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
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