Summary
Sungju Kwon is a development team lead at NAVER with 11 years of experience building high-performance Java backends and over three years focused on production recommender systems for the BAND service. He designed and operates large-scale recommender pipelines serving ~100M page views/day and previously built feed APIs handling 200–300M PV/day with sub-50ms responses. Comfortable across the ML stack (TensorFlow, Spark MLlib, Hadoop) and backend engineering (Spring, Cassandra, Memcached), he bridges model lifecycle management and low-latency system design. His background includes Android performance engineering on dodol Launcher and a track record of turning research-level models into robust, production services. Based in Gyeonggi, South Korea, he combines deep hands-on engineering with team leadership to deliver measurable product impact.
11 years of coding experience
13 years of employment as a software developer
공학학사 / BS, 컴퓨터공학 / Computer Science & Engineering, 공학학사 / BS, 컴퓨터공학 / Computer Science & Engineering at 서울대학교 / Seoul National University
Student, Deep Learning, Student, Deep Learning at Coursera
Student, Deep Learning Foundation Nanodegree, Student, Deep Learning Foundation Nanodegree at Udacity
Student, Data Science and Machine Learning with Python - Hands On!, Student, Data Science and Machine Learning with Python - Hands On! at Udemy
Korean, English