Summary
Jason Hills is a Principal Data Scientist with 12 years building end-to-end computer vision systems and distributed software, currently leading camera perception and embedded/cloud pipelines at Vivint. He blends hands-on Rust development, machine learning, and mathematical modeling to optimize production systems—from on-device inference to GCP cloud training and storage-cost tradeoffs. Jason thrives in collaborative, pair-programming environments and often serves as the bridge between domain experts and engineers, teaching practical skills like Rust in academic settings as a former university instructor. His background includes contracting work that solved real-world reliability and scaling problems (offline kiosks, SMS provisioning with Twilio) and productionizing image pipelines that improved print quality. Comfortable across full-stack, embedded, and research flavors of engineering, he brings a rare mix of theoretical rigor (math and philosophy degrees) and pragmatic product-focused delivery. An understated strength is his ability to quantify system-level tradeoffs with mathematical models that directly influence production parameter choices and cost savings.
12 years of coding experience
11 years of employment as a software developer
The University of Utah
Bachelor's Degree, Philosophy, Bachelor's Degree, Philosophy at Brigham Young University
English, Hungarian