Charles Siegel

Senior Applied Scientist at Amazon

Seattle, Washington, United States
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Summary

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Senior
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Top School
Charles Siegel is a Senior Applied Scientist with 11 years of experience applying a Ph.D. in mathematics to machine learning, distributed systems, and big data at organizations including Meta and Amazon. He specializes in scalable deep learning and large-scale training, bringing uncommon mathematical rigor to model design, optimization, and system-level performance. His background spans research roles at national labs and academia, where he extended frameworks like TensorFlow for scientific datasets and published work on efficient training techniques. At Cray and HPE he helped customers and internal teams get the most out of HPC for deep learning, and at Meta focused on internal ML engineering for production-scale systems. Now based in Seattle, he blends theoretical insight with hands-on engineering to move models from research to production across cloud and HPC environments. Outside of work he posts hobby projects on GitHub tied to games he plays, reflecting a practical curiosity that fuels his applied research.
code11 years of coding experience
job13 years of employment as a software developer
bookBachelor of Science (BS) Mathematics, Bachelor of Science (BS) Mathematics at Rutgers University
bookDoctor of Philosophy (Ph.D.) Mathematics, Doctor of Philosophy (Ph.D.) Mathematics at University of Pennsylvania
languagesEnglish, French, Japanese, German, Spanish
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Github Skills (18)

pytorch10
python10
data-science10
machine-learning10
deep-learning10
tensorflow9
jax9
science8
pure-python8
neural-network8
algebra7
computer-algebra7
math7
computer-algebra-system6
scraper1

Programming languages (1)

Python

Github contributions (5)

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matex-org/matex

Apr 2016 - Apr 2017

Contributions:21 commits, 21 pushes, 1 branch in 1 year
Website for Tellurium Games
Contributions:384 PRs, 336 pushes, 435 branches in 1 year 6 months
gamegamestellurium
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Charles Siegel - Senior Applied Scientist at Amazon