Summary
Jong Shinn is a Senior Machine Learning Engineer based in Seoul with nine years of experience building production ML systems for manufacturing, EVs, and energy applications. He has led end-to-end projects—from PoCs and technical pre-sales for US market expansion to deploying real-time anomaly detection and HVAC optimization solutions—bridging research-quality models with practical MLOps. His work spans time-series anomaly detection, battery RUL estimation, edge ML for automotive boards, and control/optimization for industrial systems, often using PyTorch, ONNX, and Azure. Notably, he authored an open-source synthetic sensor data generator (Mandrova) early in his career and has hands-on experience integrating ML into hardware and control loops. A UC Irvine-trained computer scientist with a statistics minor and military leadership experience at the DMZ, he combines disciplined teamwork with a knack for turning noisy sensor streams into deployable, energy-efficient solutions.
9 years of coding experience
6 years of employment as a software developer
Computer Science, Computer Science at Diablo Valley College
University of California, Irvine
English, Korean, Japanese