Jason Jewik is an AI Engineer based in San Francisco with a decade of experience building production ML systems and pipelines for enterprise search and LLM-powered workflows. He’s helped scale search relevance and Solr infrastructure at Box, transitioned models and data tooling into production, and now focuses on orchestrating AI-enabled work for large customers at WRITER. Jason blends academic research and applied engineering—he co-authored ClimateLearn, a NeurIPS 2023–featured project from UCLA that standardizes climate ML datasets and models. His background includes hands-on computer vision and remote sensing work, civic data pipeline projects, and early drone-deployment modeling at Boeing, reflecting a penchant for tech that addresses real-world systems and the environment. Known for bridging research and product delivery, he brings practical experience shipping models end-to-end alongside a genuine interest in tech that can help save the planet.
11 years of coding experience
6 years of employment as a software developer
High School Diploma, High School Diploma at Gretchen Whitney High School
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of California, Los Angeles
Dual Enrollment, Dual Enrollment at Cerritos College
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