James Kunstle is a machine learning engineer and research fellow with six years of experience building and scaling LLM and AI systems across industry and academia. Based in Seattle, he has led work at Red Hat on InstructLab and distributed LLM training, shifted into agentic systems optimization at Not Diamond, and now trains genomic diffusion transformer models at Fred Hutch. He combines production-focused engineering (performance, scalability, RPM tooling) with hands-on research in adversarial examples and genomics, and has taught software engineering and CS courses at Boston University. Notably, his background bridges open-source infrastructure and cutting-edge model alignment, reflecting a knack for turning research techniques into deployable systems.
6 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Boston University
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