Summary
Geunho Lee is a Staff Machine Learning Engineer based in Seoul with 11 years of experience building production-ready AI/ML systems across mobile, e-commerce, and platform teams. He led work on model efficiency and deployment at Qualcomm, contributing to AIMET and IR-level optimizations for LLMs and vision models to enable real-world scalability. Prior roles at Kakao and Coupang combined spam/anti-abuse research, query understanding, and large-scale search relevance improvements using both classical NLP and embedding-driven approaches. Trained originally in computer science with a graduate background in systematic biology, he brings a rare mix of rigorous scientific thinking and pragmatic engineering for model optimization and search systems. He’s especially focused on squeezing practical efficiency from large models and translating research techniques into robust, deployable tooling.
11 years of coding experience
8 years of employment as a software developer
Master of Science, Systematic Biology/Biological Systematics, Master of Science, Systematic Biology/Biological Systematics at Gwangju Institute of Science and Technology
Bachelor of Engineering, Computer science, Bachelor of Engineering, Computer science at Pusan National University
Korean, English