Min Kim

Co-Founder & CTO at Radiant AI

London, England, United Kingdom
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Summary

🤩
Rockstar
🎓
Top School
Min Kim is a Co-Founder and CTO with 8 years of experience building production-grade ML systems and startups, now leading Radiant AI to apply machine learning for sustainable finance. He combines deep research experience in NLP, signal processing, geometric ML and information theory with hands-on production work—previous roles include applied scientist at Amazon (improving CTR and sales) and ML research at Babylon Health and Soul Machines. Min has a strong track record shipping scalable models and infrastructure that serve millions of requests and deliver state-of-the-art results on medical and graph representation tasks. A former organizer of the Auckland Deep Learning Meetup and Oxford-trained engineer, he blends community leadership with scholarly rigor and product-focused deployment. An interesting detail: his background spans both neural TTS that reached human-like quality and interpretable medical time-series modeling, reflecting a rare mix of perceptual and clinical ML expertise.
code9 years of coding experience
job6 years of employment as a software developer
bookMaster of Science Software Engineering Computer Science, Master of Science Software Engineering Computer Science at University of Oxford
bookBachelor of Engineering (Honours) Engineering Science, Bachelor of Engineering (Honours) Engineering Science at The University of Auckland
languagesEnglish, Korean, Spanish
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Github Skills (31)

squad10
rnet10
natural-language-processing10
nlp10
artificial-intelligence9
machine-learning9
comprehension9
tensorflow9
ai9
deep-learning9
data-analysis8
datasets8
data-science8
recurrent8
neural-network7

Programming languages (5)

ShellRustTeXJavaScriptPython

Github contributions (5)

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localminimum/R-net

Aug 2017 - Apr 2018

A Tensorflow Implementation of R-net: Machine reading comprehension with self matching networks
Contributions:16 commits, 1 comment in 8 months
rnettensorflowrnnsquadqa
localminimum/QANet

Nov 2017 - May 2018

A Tensorflow implementation of QANet for machine reading comprehension
Contributions:29 commits, 1 PR, 6 pushes in 6 months
tensorflownlpsquadmachine-comprehensioncnn
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