Wenxi Li
Sr. Machine Learning Engineer at AARP
Washington, District of Columbia, United States
Summary
👤
Senior🎓
Top SchoolWenxi Li is a Senior Machine Learning Engineer with a decade of experience building production ML systems and delivering data-driven insights across finance, automotive, retail, and aging-services at AARP. She combines deep NLP and sequence-model expertise—having rebuilt a large-scale Chinese lyrics generation system with GPT-2 and 300GB of training data—with hands-on ML engineering that reduced inference time by two thirds and markedly improved fluency. At BLEND360 she translated complex analytics into actionable business strategy, automated data pipelines between Snowflake and S3, and doubled reporting productivity. Her background in industrial engineering and logistics (UC Berkeley, Tongji) informs a pragmatic approach to modeling, optimization, and supply-chain problems. Comfortable moving models from research to production, she has repeatedly partnered with stakeholders to simplify solutions to the right level of complexity for business impact. Based in Washington, D.C., she brings a mix of research-grade modeling, production automation, and user-focused translation to cross-functional teams.
10 years of coding experience
5 years of employment as a software developer
Master of Engineering - MEng, Industrial Engineering and Operations Research, Master of Engineering - MEng, Industrial Engineering and Operations Research at University of California, BerkeleyBachelor of Engineering - BE, Transportation Engineering, Bachelor of Engineering - BE, Transportation Engineering at Berkeley GlobalBachelor of Science - BS, Logistics Engineering, Bachelor of Science - BS, Logistics Engineering at Tongji University
Chinese, English, Chinese, German, French
Stackoverflow
1reputation
0reached
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Github contributions (5)
B2BDC/B2BDC
May 2016 - Jun 2017
Contributions:3 releases, 18 commits, 37 pushes in 1 year 1 month
B2BDC/Model-discrepancy-paper-examples
Jun 2019 - Jun 2019
Contributions:5 pushes, 1 branch in 2 days
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