大语言模型后训练算法工程师
Tasks
- Build and optimize model evaluation metrics
- Collaborate with data and product teams
- Define delivery standards and collect feedback
- Deploy and optimize inference services
- Design LLM reinforcement learning experiments
- Design LLM supervised fine tuning experiments
- Improve training framework stability
- Optimize cloud training pipeline efficiency
- Optimize data loading and resource scheduling
- Optimize distributed training communication
- Optimize model accuracy safety and consistency
Perks/Benefits
- N/A
Skills/Tech-stack
Distributed Training | Docker | Fine Tuning | GPU Training | Kubernetes | LLM Inference | Language Models | Large Language Models | Model Evaluation | Multi-GPU | Multi-GPU Training | PyTorch | Python | Ray Serve | Reinforcement Learning | SGLang | Supervised Fine Tuning | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
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