Summary
Sam Mcdermott is a Senior AI/ML Scientist with 11 years of experience applying advanced probabilistic inference and machine learning to astrophysics, cosmology, and industry problems. With a PhD in Physics and roles at Fermilab and the University of Chicago, he specializes in simulation-based inference, Bayesian neural networks, nested sampling and HMC, and creating novel deep architectures and optimizers. He has led collaborative, distributed research groups, mentored junior researchers, and transitioned research into production ML at startups and enterprise settings (including deployment on AWS and CI/CD pipelines). Notably, his work spans both high-citation theoretical dark-matter research and practical applied ML such as fraud detection and appointment prediction, reflecting a rare ability to bridge deep science and production impact. Based in Philadelphia, he’s now focused on bringing cutting-edge ML techniques to new datasets and problems within enterprise AI.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University of Michigan
Bachelor of Arts - BA, Physics, Bachelor of Arts - BA, Physics at University of Pennsylvania