LLM Engineer
Tasks
- Build training pipelines
- Construct and curate training datasets
- Design evaluation suites and benchmarks
- Design fine tuning experiments for large language models
- Implement parameter-efficient fine-tuning methods
- Implement safety and policy evaluations
- Manage model artifacts lineage and reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate training jobs on GPU clusters
- Optimize training throughput
- Translate research advances into production ready recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
Skills/Tech-stack
DPO | Deep learning | Distributed Training | Efficient Attention | Efficient Fine Tuning | Evaluation | FSDP | Fine Tuning | GPU clusters | Human evaluation | Language Models | Large Language Models | LoRA | Machine Learning | Mixed Precision | Parameter efficient fine-tuning | Pipeline parallelism | PyTorch | Python | QLoRA | RLHF | Reinforcement Learning | Sequence Packing | Supervised Learning | Transformers | Zero
Education
Roles
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