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Applied Machine Learning Engineer with 11+ years of industry experience leading large-scale AI, ranking and recommendation systems development across short video platform, ads, social media and fintech.
• Applied Machine Learning Engineer with 11+ years of industry experience leading large-scale AI, ranking and recommendation systems development across short video platform, ads, social media and fintech. • Proven track record of owning ambiguous ML problems end-to-end, from data and modeling through production systems and online experimentation, delivering sustained business impact. • Technical leader experienced in defining ML strategy, mentoring senior engineers, and driving cross organizational alignment across product, infra and modeling teams.
UC Irvine
Doctor of Philosophy (PhD), Applied Mathematics
N/A – Present
University of Science and techonology of china
Bachelor of Science (B.S.), Mathematics
N/A – Present
Snap Inc.
Machine Learning Engineer
April 1, 2025 – Present
Machine Learning Engineer
June 1, 2020 – April 1, 2025
SoFi
Staff Data Scientist, Modeler
October 1, 2019 – June 1, 2020
American Express
Senior Data Scientist and Machine Learning Researcher
September 1, 2014 – October 1, 2019
Greater New York City Area
Bank of America-Merrill Lynch
Data Scientist Intern
September 1, 2012 – December 1, 2012
Newport Beach, California
Cultural Fit Analysis
The candidate has a strong background in Machine Learning and Data Science across diverse industries (social media, fintech). While their technical depth is evident, their experience is heavily skewed towards ML/DS roles rather than traditional Backend Engineering. This might indicate a need for adaptation to a pure backend development culture, focusing on API design, distributed systems, and core service development, which are not explicitly highlighted in their resume. The target role 'Backend Engineer' is a significant pivot from their primary experience.
Soft Skills & Operational Fit
The candidate's experience as a technical lead and mentor at Snap Inc. suggests strong leadership, collaboration, and communication skills. Their work on driving roadmap prioritization indicates strategic thinking and operational awareness. However, specific soft skill assessments are not available.