Summary
Donghyun Hwang is a Machine Learning Engineer with 10 years' experience building end-to-end, product-focused ML systems that span data pipelines, model training, GPU-optimized inference, and on-device deployment. He has driven production face-recognition and anti-spoofing systems at scale—delivering Android calibration SDKs, stereo depth prototypes, and Triton-backed inference stacks for commercial edge devices. Previously he led AI infrastructure and biomedical signal modeling work, building a Kubernetes FaaS that cut inference latency by ~1,000× and producing a real-time preterm birth prediction prototype with 94% accuracy. Comfortable bridging research, infra, and product, he thrives on making ML reliable in constrained hardware environments and improving operational efficiency by an order of magnitude. Based in South Korea, he blends hands-on implementation with system-level optimization and a pragmatic focus on user-facing impact.
10 years of coding experience
1 year of employment as a software developer
석사, Electrical and Electronic Engineering, 석사, Electrical and Electronic Engineering at 서울과학기술대학교
Bachelor's degree, Electric, Electronic, Control Engineering, 3.23, Bachelor's degree, Electric, Electronic, Control Engineering, 3.23 at 한경국립대학교