LLM Fine-Tuning Engineer
Tasks
- Apply parameter efficient fine tuning techniques
- Build training pipelines using distributed training frameworks
- Conduct safety refusal and policy evaluations
- Construct curate and QA training datasets
- Design fine tuning experiments for large language models
- Document training methodology and results
- Implement evaluation suites with automated and human evaluation
- Manage model artifacts and ensure reproducibility
- Mentor engineers on fine tuning evaluation and deployment
- Operate GPU cluster training jobs and recover training state
- Optimize training throughput with mixed precision and efficient attention
- Translate LLM research into production ready fine tuning recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
- N/A
Skills/Tech-stack
Adapter | Attention Optimization | DPO | Distributed Training | Evaluation benchmarks | FSDP | Fine Tuning | GPU clusters | Human evaluation | Hyperparameter Tuning | Language Models | Large Language Models | LoRA | Mixed Precision | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RLHF | Red Teaming | Sequence Packing | Supervised Fine Tuning | Transformer | Zero
Education
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