Kevin Jo
Lead Product Engineer at 오토피디아
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolKevin Jo is a Lead Product Engineer based in Seoul with eight years of experience building production-grade AI, MLOps, and cloud-native infrastructure for automotive inspection and data products. He co-created and commercialized Dr.Tread, the world’s first tire wear prediction API, while architecting on-prem GPU K8s clusters, BigQuery data warehouses, and dbt-powered analytics to deliver scalable ML services. Kevin has a unique blend of mechanical engineering and physics training from KAIST and hands-on software skills that let him bridge robotic vehicle inspection hardware with data-driven software. He also drove a 56x organic MAU increase through automated SEO and internal linking strategies, and has practical open-source experience from deep learning seminar work that emphasizes reproducible notebooks and cloud execution. Ambitious about redefining vehicle transparency, he focuses on turning complex sensor and maintenance data into trustworthy buyer-facing products.
8 years of coding experience
2 years of employment as a software developer
Physics, Physics at 한국과학기술원(KAIST) 부설 한국과학영재학교Bachelor of Science, Computer Science / Mechanical Engineering, Bachelor of Science, Computer Science / Mechanical Engineering at 한국과학기술원(KAIST)
Github Skills (4)
jupyter-notebook10
google-colab10
documentation7
machine-learning4
Programming languages (9)
Github contributions (5)
heartcored98/Standalone-DeepLearning
Jan 2019 - Jul 2022
2019 KAIST 딥러닝 홀로서기 세미나용 저장소입니다.
Role in this project:
Student (Deep Learning Practitioner)
Student (Deep Learning Practitioner)Contributions:107 commits, 108 pushes, 1 branch in 3 years 6 months
Contributions summary:Kevin's contributions are focused on updating the instructions within a Jupyter Notebook related to a linear regression lab. The edits involve clarifying the process of executing the notebook within Google Colab and adding a link to the notebook. The code differences do not involve modification of machine learning model implementation but rather relate to the operational instructions of using the notebook in a cloud environment and formatting.
deep-learningpytorchkaisttensorflow
heartcored98/COMET-pytorch
Nov 2018 - Feb 2020
COMET(Chemically Omnipotent Molecular Encoder from Transformer)
Contributions:137 commits, 8 PRs, 101 pushes in 1 year 2 months
transformercometencodermolecular
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.