Summary
Kevin Henner is an independent full-stack ML engineer with 12 years of software experience and four years focused on taking ML and NLP projects from zero to one, shipping production apps that combine in-house models and leading LLMs. He’s comfortable starting from a blank slate—no data, repo, or cloud account—and rapidly builds end-to-end systems using PyTorch, Hugging Face, LangChain, FastAPI, React, and Pulumi, plus MLOps tooling like SageMaker and Weights & Biases. As a founding ML engineer at Contenda and prior NLP roles, he led rigorous CI/CD and testing practices while integrating multi-generation LLM prompting and model chaining into user-facing products. His background in computational linguistics and anthropology informs a thoughtful approach to which cognitive tasks should be offloaded to technology and how to surface model insights effectively to users. Now operating solo on a stealth project in Seattle, he combines product sensibility with a historian’s attention to how tools reshape skills and knowledge.
12 years of coding experience
8 years of employment as a software developer
Master of Science in Computational Linguistics Computational Linguistics, Master of Science in Computational Linguistics Computational Linguistics at University of Washington
University of California, San Diego
Summer Fellowship, Summer Fellowship at University of Michigan - School of Information
BA Anthropology, BA Anthropology at Reed College
tok pisin, Russian, French