LLM Fine-Tuning Engineer
United States - Remote
R
USD 150K-270K (estimate) Mid-level Full Time
Tasks
- Apply parameter efficient fine tuning with LoRA QLoRA and adapters
- Build scalable distributed training pipelines
- Collaborate with product and research on fine tuning roadmaps
- Construct curate and QA training datasets
- Design evaluation suites with benchmarks and human evaluation
- Design fine tuning experiments for large language models
- Document training methodology and results
- Execute supervised fine tuning workflows
- Implement preference optimization with DPO and RLHF
- Implement safety refusal and policy evaluations
- Manage model artifacts lineage and reproducibility
- Mentor engineers on fine tuning evaluation and deployment
- Operate training jobs on GPU clusters and recover failed runs
- Optimize training throughput with mixed precision sequence packing and efficient attention
- Tune hyperparameters and optimizer configurations
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | Direct Preference Optimization | Distributed Training | Efficient Attention | FSDP | Human Feedback | Hyperparameter Tuning | Learning from Human Feedback | LoRA | Mixed Precision | Mixed-precision training | Model Evaluation | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | Reinforcement Learning | Reinforcement Learning from Human Feedback | Safety evaluation | Sequence Packing | Supervised Learning | Transformers | Zero
Education
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