LLM Engineer
Tasks
- Build training pipelines
- Collaborate with cross-functional teams
- Construct instruction and preference datasets
- Design fine tuning experiments for large language models
- Document training methodology and results
- Implement evaluation suites
- Implement parameter efficient fine tuning
- Implement safety and policy evaluations
- Manage model artifacts and reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate training jobs on GPU clusters
- Optimize training throughput
- Translate LLM research into production recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
Skills/Tech-stack
Adapter methods | DPO | DeepSpeed ZeRO | Distributed Training | Efficient Attention | FSDP | Fine Tuning | Human Feedback | Language Models | Large Language Models | Learning from Human Feedback | LoRA | Mixed Precision | Pipeline parallelism | Preference optimization | PyTorch | Python | QLoRA | RLHF | Reinforcement Learning | Reinforcement Learning from Human Feedback | Sequence Packing | Supervised Learning | Transformer Models
Education
Roles
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