LLM Fine-Tuning Engineer
Tasks
- Apply parameter efficient fine tuning techniques
- Build and curate instruction tuning datasets
- Build scalable training pipelines
- Collaborate with cross functional teams on fine tuning roadmaps
- Design fine tuning experiments for large language models
- Document training methodology and results
- Implement automated and human evaluation suites
- Implement safety refusal and policy evaluations
- Manage model artifacts lineage and reproducibility
- Mentor engineers on fine tuning and evaluation best practices
- Operate distributed training jobs on GPU clusters
- Optimize training throughput with mixed precision and attention optimizations
- Tune hyperparameters and optimizer configurations
Perks/Benefits
Skills/Tech-stack
Adapter methods | Attention Optimization | DPO | Deep learning | FSDP | GPU clusters | LoRA | Machine Learning | Mixed Precision | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RLHF | Reinforcement Learning | Sequence Packing | Supervised Learning | Transformer Models | Zero
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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