LLM Fine-Tuning Engineer
Tasks
- Build scalable distributed training pipelines
- Construct and curate training datasets
- Design evaluation suites with benchmarks and human evaluation
- Design fine tuning experiments for large language models
- Implement parameter efficient fine tuning
- Implement safety and policy evaluations
- Manage model artifacts and reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate large scale GPU training jobs
- Optimize training throughput with mixed precision and efficient attention
- Translate research advances into production recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
- N/A
Skills/Tech-stack
Adapters | Benchmarking | DPO | Deep learning | Efficient Fine Tuning | Evaluation methodology | FSDP | Fine Tuning | GPU clusters | Human evaluation | LoRA | Mixed Precision | Parameter efficient fine-tuning | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RLHF | Red Teaming | Safety evaluation | Sequence Packing | Supervised Fine Tuning | Transformer | Zero
Education
Roles
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