Yan Zhang
Principal AI ML Engineer at Fidelity Investments
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolYan Zhang is a Principal AI/ML Engineer based in Boston with 10+ years of experience building production-ready machine learning and agentic AI systems across industry and cloud platforms. He has led applied research and deployment at Microsoft—improving LLM behavior with techniques like DPO, data augmentation, and few-shot engineering—and now drives AI strategy at Fidelity. Yan combines a strong research foundation (PhD in Computer Science) with hands-on engineering: fine-tuning small language models for manufacturing nomenclature, building web-scraping and compliance-check agents, and conducting rigorous error analysis to lift real metrics. He contributes to community best practices through documentation work on a popular recommenders repo, emphasizing clarity and reproducibility. Known for bridging experimentation and productization, Yan routinely translates novel ML methods into measurable improvements in safety, reliability, and developer productivity.
10 years of coding experience
17 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of VermontBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Nankai University
Github Skills (3)
recommender-system10
documentation10
python5
Programming languages (5)
Github contributions (5)
recommenders-team/recommenders
May 2021 - Oct 2021
Best Practices on Recommendation Systems
Role in this project:
Technical Writer
Technical WriterContributions:72 reviews, 103 commits, 17 PRs in 4 months
Contributions summary:Yan's commits primarily focus on updating and modifying documentation files within the repository. These changes involve edits to `.rst` files, including restructuring content, adding modules, and updating references. The edits span various documentation files related to recommenders, datasets, and other core components of the project. The user also refactored the documentation to improve formatting and readability.
recommendation-systemspythonjupyter-notebookoperationalizationmicrosoft
microsoft/deploy-MLmodels-on-iotedge
Sep 2019 - Oct 2019
This repository shows how to deploy machine learning models on Azure IoT Edge.
Contributions:45 commits, 2 PRs, 28 pushes in 18 days
watsoncmlazure-iotmlmlops
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