Zach Raymer is a senior machine learning engineer with nine years of geospatial and remote sensing experience, currently leading a small team at Planet to apply hyperspectral imagery for utility clients. He builds production-ready Python tooling and leverages cutting-edge open-source DL methods to accelerate analytics—often turning week-long model cycles into single-day iterations. His background spans satellite object detection, hyperspectral processing, and workflow automation at companies like Maxar and Quantum Spatial, where he architected multi-million dollar programs and reduced compute times by up to 30%. Zach pairs field-validated research on Great Lakes water quality with practical engineering, routinely translating academic algorithms into scalable client solutions. Based in Cedar, Michigan, he’s known for porting legacy remote-sensing workflows into modern pipelines, a less obvious strength that consistently drives operational efficiency.
9 years of coding experience
7 years of employment as a software developer
Masters of Science, Geographic Information Science, Masters of Science, Geographic Information Science at Central Michigan University
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Zach Raymer - Sr. Machine Learning Engineer at Planet