LLM Fine-Tuning Engineer
Tasks
- Apply parameter efficient fine tuning
- Build dataset curation and quality processes
- Collaborate on fine tuning roadmaps
- Design and execute fine tuning experiments
- Design evaluation suites
- Document training methodology and results
- Implement distributed training pipelines
- Implement safety and policy evaluations
- Manage model artifacts and reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate training jobs on GPU clusters
- Optimize training throughput
- Stay current with LLM research
- Tune hyperparameters and training stability
Perks/Benefits
Skills/Tech-stack
Adapter-Tuning | Automated Benchmarks | DPO | Distributed Training | Evaluation methodology | FSDP | GPU Computing | Human evaluation | Hyperparameter Tuning | Language Models | Large Language Models | LoRA | Mixed Precision | Pipeline parallelism | PyTorch | Python | QLoRA | RLHF | Red Teaming | Reinforcement Learning | Safety evaluation | Sequence Packing | Supervised Learning | Transformer | Zero
Education
Roles
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