LLM Fine-Tuning Engineer
Tasks
- Align fine tuning roadmaps with business needs
- Apply parameter efficient fine tuning
- Build dataset curation and quality assurance
- Build evaluation suites
- Design fine tuning experiments
- Document training methodology and results
- Implement safety and policy evaluations
- Implement training pipelines
- Manage model artifacts and reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate GPU cluster training jobs
- Optimize training throughput
- Translate LLM research into production recipes
- Tune hyperparameters and optimizers
Perks/Benefits
Skills/Tech-stack
Attention Optimization | Benchmarking | Direct Preference Optimization | Distributed Training | FSDP | GPU Computing | Human Feedback | Human evaluation | Learning from Human Feedback | LoRA | Mixed Precision | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | Reinforcement Learning | Reinforcement Learning from Human Feedback | Reproducibility | Sequence Packing | Supervised Learning | Transformer | Zero
Education
Roles
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