NLP AI Engineer
Tasks
- Build scalable training pipelines with distributed frameworks
- Collaborate with cross functional teams on fine tuning roadmaps
- Design evaluation suites with benchmarks and human evaluation
- Design fine tuning experiments for large language models
- Document training methodology and results
- Implement parameter-efficient fine-tuning methods
- Implement safety refusal and policy evaluations
- Lead dataset construction curation and quality assurance
- Manage model artifacts lineage tracking and reproducibility
- Mentor engineers on fine tuning and evaluation rigor
- Operate large scale training jobs on GPU clusters
- Optimize training throughput with mixed precision
- Translate LLM research into production fine tuning recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
- N/A
Skills/Tech-stack
Adapters | DPO | Efficient Fine Tuning | Evaluation | FSDP | Fine Tuning | GPU clusters | Human evaluation | Language Models | Large Language Models | LoRA | Mixed Precision | Parameter efficient fine-tuning | Pipeline parallelism | Policy Evaluation | Preference optimization | PyTorch | Python | QLoRA | RLHF | Red Teaming | Reinforcement Learning | Safety evaluation | Sequence Packing | Supervised Learning | Transformers | Zero
Education
Roles
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