Ryan Koo
Software Engineer at NVIDIA
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolRyan Koo is a software engineer at NVIDIA and a fourth-year Computer Science student at Cornell with nine years of hands-on experience building backend systems and developer tools. He focuses on ML/AI and large-scale data infrastructure, notably contributing to AIStore—a widely used scalable storage project for AI workloads—where he led development of the Python SDK, cluster health APIs, and a CLI-driven benchmarking tool. His internships at NVIDIA evolved into a full-time role, reflecting deep domain knowledge in object storage, ETL runtime support, and integrating storage with training workflows. Ryan pairs production engineering with practical research experience from Cornell’s ChemE Car team, where he built sensor-driven Arduino tools and helped win regional competitions. Based in New York, he brings a pragmatic, open-source-first approach to solving performance and operability challenges at petascale. Outside work he pursues street photography, automotive racing, and basketball, interests that inform his eye for systems detail and real-world experimentation.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Cornell UniversityPre-College, Engineering, Pre-College, Engineering at Carnegie Mellon UniversityHigh School Diploma, High School Diploma at Korea International School
English, Korean
Github Skills (10)
develop10
api10
back-end-development10
apidoc10
python10
unit-testing9
object-storage9
kubernetes8
kubernetes-pods8
documentation7
Programming languages (6)
Github contributions (5)
NVIDIA/aistore
Jun 2022 - Aug 2022
AIStore: scalable storage for AI applications
Role in this project:
Back-end Developer
Back-end DeveloperContributions:37 commits, 2 PRs, 6 pushes in 2 months
Contributions summary:Ryan Koo's contributions center around developing and maintaining the Python SDK for the AIStore project. He implemented a cluster health API, added documentation, reorganized tests, and ported bucket renaming functionality. He also restructured and refactored the API code related to bucket and cluster operations, and object management.
scalabledeep-learningdistributed-shufflemachine-learninghyper-converged
rkoo19/USACO-Feburary-2018
Jun 2018 - Nov 2020
Contributions:1 push, 1 branch in 2 years 5 months
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