Summary
Jung Ko is a Principal Machine Learning Architecture Engineer with 15 years of experience designing, implementing, and bringing up ML inference chips and field-programmable devices from concept to silicon. He blends deep hardware expertise in advanced process nodes (14nm–22nm) and FPGA fabrics with software skills in compiler/assembler development, cycle-accurate simulation, device drivers, and embedded inference libraries. At Perceive he led end-to-end delivery of a novel edge ML inference chip—authoring the initial toolchain and CI for hardware/software verification—and now applies that systems-level thinking at Rivian. Known for solving hard timing-closure and silicon bring-up problems, he also builds in-house CAD and verification tools to accelerate iteration. Based in California, he combines academic rigor (MSc ECE) with hands-on lab and production experience across startups and tier-one semiconductor teams.
15 years of coding experience
20 years of employment as a software developer
MSc, Electrical and Computer Engineering, MSc, Electrical and Computer Engineering at University of Alberta
BEng, Electrical Engineering, BEng, Electrical Engineering at Concordia University
English, Chinese, Spanish