【26届校招】大语言模型后训练算法工程师（Foundation Model）
Tasks
- Build and optimize model evaluation metrics
- Collaborate with data and product teams for delivery feedback
- Deploy LLM services on Kubernetes
- Design LLM supervised fine tuning experiments
- Implement RLHF and LLM reinforcement learning
- Implement multi machine distributed training communication
- Optimize LLM fine tuning pipeline efficiency
- Optimize LLM inference serving performance
- Schedule training resources and ensure stability
Perks/Benefits
- N/A
Skills/Tech-stack
Axolotl | Cloud Computing | Data loading | Distributed Training | Docker | Fine Tuning | Kubernetes | LLM Evaluation | LLM Inference | Language Models | Large Language Models | Machine communication | Model Deployment | Multi Machine Communication | PyTorch | Python | RLHF | Ray Serve | Reinforcement Learning | Resource scheduling | SGLang | Supervised Fine Tuning | Trinity RFT | VLLM | VeRL
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
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