LLM Engineer
Tasks
- Build scalable training pipelines
- Construct and curate datasets for instruction tuning and preference data
- Design and execute evaluation suites
- 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 training jobs on GPU clusters
- Optimize training throughput with mixed precision and efficient attention
- Translate LLM research into production ready recipes
- Tune hyperparameters and training stability strategies
Perks/Benefits
Skills/Tech-stack
Adapter-Tuning | DPO | Dataset curation | DeepSpeed ZeRO | Efficient Attention | Evaluation | FSDP | Fine Tuning | GPU Computing | Human evaluation | LoRA | Mixed Precision | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RLHF | Safety evaluation | Sequence Packing | Supervised Learning | Transformer
Education
Roles
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