Michael Schmidt

Principal ML Engineer at Ix

Denver, Colorado, United States
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Summary

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Senior
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Top School
Michael Schmidt is a Principal ML Engineer in Denver with 12 years of experience building mathematically rigorous, production-ready AI systems that prioritize interpretability and uncertainty quantification. He specializes in Bayesian methods—Gaussian processes, change-point detection, and probabilistic novelty detection—and has applied them across agriculture, healthcare, law, and finance to deliver actionable forecasts and decision tools. At Redpoll and Ix he led DARPA-linked research and deployed models for time-series inference and reinforcement learning under uncertainty, while at CiBO delivered a crop-yield forecast with industry-leading accuracy. With an MS in Physics, ongoing PhD work in Applied Mathematics, and a background spanning DevOps, teaching, and high-performance computing, he blends deep theory with pragmatic engineering. Colleagues describe him as a researcher-engineer who turns complex probabilistic ideas into transparent tools for real-world impact.
code12 years of coding experience
job10 years of employment as a software developer
bookDoctor of Philosophy - PhD Applied Mathematics, Doctor of Philosophy - PhD Applied Mathematics at University of Colorado Denver
bookMS Physics, MS Physics at University of Colorado Boulder
languagesEnglish, Latin
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Github Skills (48)

raid10
fat9
lvm9
luks9
rescue9
child-process9
decimal9
dub9
bayesian8
initramfs8
filemaker8
identifier7
low-level7
breeze7
shell6

Programming languages (7)

C++ShellRustScalaHTMLJupyter NotebookPython

Github contributions (5)

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schmidmt/rmcmc

Aug 2018 - Mar 2020

Contributions:27 commits, 13 pushes, 5 branches in 1 year 8 months
Contributions:9 commits, 3 pushes in 1 year 8 months
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