Jiyang Kang
Technical Program Manager at Google
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolJiyang Kang is a Technical Program Manager with nine years focused on scaling machine learning and cloud infrastructure for large-model training, currently based in Mountain View and working at Google. He has a strong track record at AWS and Google driving ML solutions, from hands-on deep learning architecture and HPO pipelines in SageMaker to managing cross-functional teams across APAC and the U.S. Jiyang combines deep academic training—a Ph.D. in EECS from Seoul National University—with practical systems engineering experience dating back to Samsung and semiconductor R&D. He specializes in removing data bottlenecks to maximize compute utilization and has contributed open-source lab material and HPO implementations that make distributed training more accessible. Known for bridging research, product, and infra, he brings both strategic program leadership and the ability to implement low-level ML engineering improvements. Fluent in navigating global orgs, he often pairs technical ownership with localized developer enablement, as evidenced by his contributions to a Korean AWS AI/ML workshop.
10 years of coding experience
23 years of employment as a software developer
Stanford LEAD Professional Certificate Business/Executive Leadership, Stanford LEAD Professional Certificate Business/Executive Leadership at Stanford University Graduate School of BusinessDoctor of Philosophy (Ph.D.) EECS / 전기컴퓨터공학부, Doctor of Philosophy (Ph.D.) EECS / 전기컴퓨터공학부 at Seoul National University
English, Korean
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
hyperparameter-tuning10
machine-learning10
aws10
tensorflow10
python10
sagemaker10
deeplearning-ai9
deep-learning9
algorithms8
Programming languages (4)
Github contributions (5)
aws-samples/aws-ai-ml-workshop-kr
Oct 2018 - Nov 2018
A collection of localized (Korean) AWS AI/ML workshop materials for hands-on labs.
Role in this project:
ML Engineer
ML EngineerContributions:11 commits, 8 pushes in 24 days
Contributions summary:Jiyang's primary contribution involved creating and integrating a Hyperparameter Tuning (HPO) job within the SageMaker environment. The commits show the creation of Lab 3, which focuses on Hyperparameter Tuning using SageMaker TensorFlow container with distributed training using the MNIST dataset and the file `mnist_hpo.py` illustrates the code. The commits also show modifications in existing modules such as module 5 and 6, indicating work on the automated model tuning.
aiawsmachine-learningsagemakerml
jamiekang/gluoncv-hol
Sep 2019 - Sep 2019
Contributions:27 commits, 10 pushes in 14 days
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.