LLM Fine-Tuning Engineer
United States - Remote
R
USD 150K-270K (estimate) Mid-level Full Time
Tasks
- Align fine tuning roadmaps with business needs
- Apply parameter efficient fine tuning techniques
- Build scalable distributed training pipelines
- Build supervised preference and reinforcement learning fine tuning workflows
- Construct curate and QA training datasets
- Design fine tuning experiments for large language models
- Document training methodology results and decisions
- Implement evaluation suites with benchmarks and human evaluation
- Implement safety refusal and policy evaluations
- Manage model artifacts lineage and reproducibility
- Mentor engineers on fine tuning and evaluation best practices
- Operate training jobs on GPU clusters and recover failures
- Optimize training throughput with mixed precision and sequence packing
- Translate LLM research into production fine tuning recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
Skills/Tech-stack
Adapter-Tuning | DPO | Dataset curation | Distributed Training | Evaluation methodology | FSDP | GPU clusters | Human evaluation | Hyperparameter Tuning | LoRA | Mixed Precision | Pipeline parallelism | Policy Evaluation | PyTorch | Python | QLoRA | RLHF | Red Teaming | Reproducibility | Safety evaluation | Sequence Packing | Transformers | Zero
Education
Roles
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