Sr. Lead AI Engineer, Data

📋 Description

• Build end-to-end model fine-tuning pipeline: data prep, training, eval, and registry.
• Implement and optimize fine-tuning techniques (QLoRA, LoRA, PEFT) for training.
• Design and maintain evaluation harnesses with task benchmarks and regression tests.
• Drive training iterations: analyze results, diagnose failures, improve data/config.
• Implement experiment tracking, hyperparameter tuning, and reproducible workflows.
• Collaborate on training data strategy with data engineering, including synthetic data.

🎯 Requirements

• 10+ years software engineering; 4+ years in ML/NLP systems.
• Hands-on fine-tuning of LLMs with parameter-efficient methods.
• Transformers architectures, tokenization, training optimization.
• Production ML training pipelines with experiment tracking.
• Python, PyTorch, distributed training; GPU-based cloud infra.
• RLHF/DPO alignment experience a plus; BS/MS in CS/ML or equivalent.

🎁 Benefits

• Pioneering technology driving efficiency.
• Collaborative culture with transparency.
• Global impact across clients and teams.
• Learn more on Life at Coupa.