Chiyoung Song
Machine Learning Research Engineer at NAVER Corp
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolChiyoung Song is a Machine Learning Research Engineer based in Seoul with 11 years of experience building production-grade computer vision systems, specializing in face recognition and image search. Currently leading image and vision initiatives at NAVER/LINE+, he has shipped face-recognition models for secure building access and payment authorization as well as AI-driven background generation for product advertising. Previously at NHN he developed visual similarity search for fashion, taught GAN workshops publicly and to government programs, and worked across TensorFlow/PyTorch and C++ pipelines. He blends research rigor from an MS in Computer Vision (Keio University) with hands-on engineering smarts honed at mobile and cloud-focused roles earlier in his career. Known for a deep curiosity about technically elegant solutions—“tech makes me insane, in the best way”—he navigates both prototyping and production deployment. Practical, cross-disciplinary, and experienced in taking models from concept to customer-facing systems.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Science (B.S.), Computer engineering, Bachelor of Science (B.S.), Computer engineering at University of WashingtonMaster of Science (M.S.), Computer Vision, Interactive Media, Master of Science (M.S.), Computer Vision, Interactive Media at 慶應義塾大学 / Keio University
Korean, English, Japanese
Github Skills (28)
openstreetmap10
tiled10
chatgpt10
dijkstra10
agentic10
autogen10
astar10
ai10
nominatim9
traveling-salesman9
directions9
map-matching9
sphinx9
osrm9
cpp8
Programming languages (3)
Github contributions (5)
SongChiYoung/Own-Logo
Feb 2015 - Jul 2018
Contributions:4 commits, 3 pushes, 2 comments in 3 years 5 months
YBIGTA/DLB
Jan 2018 - Jul 2018
Contributions:25 commits, 21 pushes, 1 branch in 5 months
deep-learningteam-datasciencedatascience
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