Mark Chan
Executive Director, AI ML Engineering at JPMorgan Chase & Co.
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolMark Chan is an engineering executive who builds and ships production-grade AI/ML platforms at enterprise scale, currently leading multi-tenant, secure cloud compute for thousands of data scientists at JPMorgan Chase. With 11 years of experience spanning startups and finance, he has been a tech lead and founding engineer on first- and second-generation AI/ML compute platforms and regularly drives 0-1 product development from ideation to deployment. He combines hands-on expertise in supervised/unsupervised learning, RAG, API and UI/UX design for AI, and rigorous test automation—evidenced by contributions to the widely used H2O-3 open-source ML project. Known for attracting and growing top engineering talent, he aligns technical roadmaps with business impact across lines of business and CTO offices. Trained in computer engineering and quantitative finance, he brings a rare blend of deep engineering craft, product sensitivity, and financial domain rigor.
11 years of coding experience
6 years of employment as a software developer
Master of Financial Engineering Quantitative Finance, Master of Financial Engineering Quantitative Finance at UCLA Anderson School of ManagementMS Financial Analysis, MS Financial Analysis at University of San FranciscoBachelor's Degree Computer Engineering, Bachelor's Degree Computer Engineering at University of Illinois Urbana-Champaign
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
automated-tests10
h2o10
python10
test-automation10
machine-learning8
data-science7
Programming languages (5)
Github contributions (5)
h2oai/h2o-3
Oct 2015 - Jul 2017
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:
Backend Developer & Test Automation Engineer
Backend Developer & Test Automation EngineerContributions:134 commits, 49 PRs, 188 pushes in 1 year 8 months
Contributions summary:Mark's commits primarily involve testing and code modification within the `h2o-3` repository, a fast and scalable machine learning platform. They executed and modified test scripts. These commits show an interest in automated testing of the h2o-py module for testing. The user appears to be contributing to ensuring the quality and functionality of H2O's Python API through testing.
xgboostgampythonk-meansautoencoders
mklechan/IBAlgoTrading
Jan 2015 - Sep 2015
Contributions:13 commits, 10 pushes in 8 months
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