Daniel Jiang

New York City Metropolitan Area United States
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Summary

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Senior
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Top School
Daniel Jiang is a machine learning and software engineer with a decade of experience bridging foundational research and production systems across academia and industry. He has worked on ML and statistical research at UC Berkeley labs and ICSI, and applied those skills to large-scale problems at Amazon, Google Research, Zoox, and Cruise, focusing on search ranking, long-context LLM memory, real-time OOD detection, and perception for autonomous systems. Comfortable in both research and engineering roles, he brings rigorous theory (provable hypothesis testing, contextual bandits) to practical deployments like extreme classification and multimodal models. Now based in the New York City area and currently a Member of Technical Staff at Anthropologie, he blends deep academic mentorship (Jordan, Dhillon, Morgenstern) with hands-on product impact. An underplayed strength is his pattern of moving between cutting-edge research groups and fast-paced product teams, enabling rapid translation of novel algorithms into scalable systems.
code10 years of coding experience
job4 years of employment as a software developer
bookBachelor's Degree Computer Science, Bachelor's Degree Computer Science at University of California, Berkeley
bookMaster’s Degree Computer Science, Master’s Degree Computer Science at University of Washington
languagesEnglish
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Stackoverflow

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Github Skills (10)

jekyll9
react5
deep-learning4
privacy1
ios1
hypothesis-testing1
scanning1
nextjs1
bootstrap1
security1

Programming languages (7)

CSSShellSCSSJavaScriptHTMLJupyter NotebookPython

Github contributions (5)

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Contributions:122 pushes, 7 branches, 2 issues in 5 years 1 month
Contributions:50 commits, 3 pushes in 1 month
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