LLM Engineer
Tasks
- Apply RLHF and DPO preference optimization
- Conduct code review and design review
- Construct and prepare training datasets
- Design fine tuning workflows for large language models
- Execute fine tuning using supervised preference and reinforcement learning
- Implement distributed training strategies
- Implement evaluation methodology for language model performance
- Mentor junior engineers
- Operate training pipelines on GPU clusters
- Recover from training job failures
Perks/Benefits
Skills/Tech-stack
DPO | Data Generation | Dataset Construction | Dataset Distillation | Deep learning | Distributed Training | Evaluation methodology | FSDP | Fine Tuning | GPU clusters | Human evaluation | Pipeline parallelism | PyTorch | Python | RLHF | Red Teaming | Responsible AI | Synthetic Data Generation | Synthetic data | Transformer | Zero
Education
Roles
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