Garrett Moore is a software engineer with 8 years of experience at the intersection of AI/ML, computational biology, and full-stack engineering, currently building ML infrastructure at Waymo in Los Angeles. He has a strong track record of turning research-grade problems into production-ready systems—at ProsperDNA he compressed genotype data 3000x, boosted inference speed 1000x, and raised multiclass accuracy by 80% while enabling cost savings. Comfortable spanning product to infrastructure, Garrett designs reusable benchmarking pipelines, end-to-end web apps with databases, and pragmatic automation that saved his team hours daily. He brings hands-on teaching experience from UC Berkeley’s CS61BL labs and a Berkeley EECS degree that underpins his technical rigor. Notably, Garrett blends domain knowledge in synthetic/ computational biology with scalable software practices, making him adept at shipping efficient ML and data solutions for real-world scientific problems.
8 years of coding experience
Bachelor's degree, Electrical Engineering and Computer Science, Bachelor's degree, Electrical Engineering and Computer Science at University of California, Berkeley
Contributions:23 PRs, 49 pushes, 20 branches in 4 years 11 months
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