LLM Fine-Tuning Engineer
Tasks
- Apply parameter-efficient fine-tuning methods
- Build dataset construction and quality assurance pipelines
- Collaborate with cross functional teams on fine tuning roadmaps
- Design evaluation suites with automated and human evaluation
- Design fine tuning experiments for large language models
- Document training methodology and results
- Implement safety refusal and policy evaluation
- Implement scalable training pipelines for transformer models
- Manage model artifacts and ensure reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate training jobs on GPU clusters
- Optimize training throughput with mixed precision and efficient attention
- Stay current with LLM research and productionize training recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
Skills/Tech-stack
Automated Benchmarks | DPO | FSDP | GPU clusters | Human evaluation | Language Models | Large Language Models | LoRA | Mixed Precision | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RLHF | Reinforcement Learning | Safety evaluation | Sequence Packing | Supervised Learning | Transformer | Zero
Education
Roles
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