Naotoshi Seo
Executive Officer & CTO at 株式会社ZOZO
Yokohama, Japan
Summary
🤩
Rockstar🎓
Top SchoolNaotoshi Seo is an executive technology leader and CTO with 14 years of experience designing Web, Data, and AI platforms, currently leading engineering and SRE at ZOZO in Yokohama. He combines hands-on backend and infrastructure expertise with executive strategy—spawning MLOps, PF-SRE, and EC platform teams while serving as CTO and VPoE. A long-time OSS committer to projects like Ruby, Fluentd, Chainer and CuPy, he has contributed deep backend, CUDA memory management and numerical-computation work that powers GPU-accelerated ML frameworks. His career spans highly trafficked game and e-commerce systems at DeNA and ZOZO, where he built monitoring, ETL, BI and AI infrastructure used across dozens of projects. Known for pragmatic optimizations (e.g., stream-aware GPU memory pools and ChainerX integration), he blends numerical rigor with production reliability. He holds an MS in ECE and a top-ranked CS bachelor’s degree, bringing both research-caliber insight and operational discipline.
14 years of coding experience
10 years of employment as a software developer
The University of Maryland, College Parkbachelor, Computer Science, 3.97 / 4.00, bachelor, Computer Science, 3.97 / 4.00 at 会津大学
Stackoverflow
11reputation
407reached
1answer
0questions
Github Skills (73)
programming-language10
csv-parse10
python10
testing10
command-line-interface10
ruby10
javas10
data-loading10
numerics10
gpu10
cython10
csv-parsing10
fluentd10
computation10
rubygems10
Programming languages (11)
Github contributions (5)
geminabox/geminabox
Apr 2016 - May 2021
Really simple rubygem hosting
Role in this project:
Back-end Developer
Back-end DeveloperContributions:111 commits, 65 PRs, 99 pushes in 5 years 2 months
Contributions summary:Naotoshi primarily contributed to improving the RubyGem hosting functionality of the geminabox repository. They refactored code, addressing deprecated warnings and updating API dependencies to enhance the application's efficiency. Their work also included security improvements and the introduction of a lock mechanism to prevent concurrent reindexing issues, indicating a focus on code quality, performance, and reliability. Further contributions show improvements to the user interface, and dependency handling.
hostingrubygemsrailsrubyrubygem
chainer/chainer
Jun 2017 - Dec 2018
A flexible framework of neural networks for deep learning
Role in this project:Back-end Developer & Machine Learning Engineer
Back-end Developer & Machine Learning EngineerContributions:1798 commits, 10 PRs, 1 push in 1 year 5 months
Contributions summary:Naotoshi primarily contributed to the development of ChainerX, focusing on integrating operations with NumPy and CUDA backends. They implemented and refined various mathematical and array manipulation functions within the library, demonstrating a strong understanding of linear algebra and numerical computation. Additionally, the user improved memory management and performance within the CUDA context, indicating work in optimization and backend implementation. Furthermore, their contributions include tests, highlighting a commitment to ensuring the accuracy and efficiency of the numerical computations.
deep-learningneural-networkpythonneural-networksmachine-learning
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