Jing Lu

Software Engineer, Machine Learning at Google DeepMind

San Francisco, California, United States
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Summary

👤
Senior
🎓
Top School
Jing Lu is a software engineer specializing in machine learning with 12 years of experience building production-grade recommender systems and predictive models. Currently at Google DeepMind, she works on integrating Gemini into consumer workflows and previously improved creator tooling at YouTube, after leading recommender efforts at Roku. Her background blends a PhD in Bioinformatics and an MS in Computer Science, enabling a rare mix of domain expertise in biological data and large-scale ML engineering. At Walmart Labs she scaled bidding and propensity pipelines to serve hundreds of millions of predictions with measurable performance gains, and earlier research roles applied statistical and computational methods to protein structure and diagnostics. She combines research rigor with product-focused execution, often automating pipelines and deploying real-time monitoring for high-throughput systems. Based in San Francisco, she brings both deep scientific training and practical systems experience to recommender and prediction problems.
code13 years of coding experience
job9 years of employment as a software developer
bookPhD Bioinformatics, PhD Bioinformatics at University of Michigan Medical School
bookMaster of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at Georgia Institute of Technology
bookB.S. Applied Physics, B.S. Applied Physics at Nankai University
languagesEnglish, Chinese
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Github Skills (166)

parallel10
python10
datasets10
r10
statistics10
gradient-boosting10
lightgbm10
kaggle10
r-package10
data-science10
classification10
decision-tree10
data-analysis10
data-mining10
machine-learning10

Programming languages (12)

TypeScriptJavaRShellC++CoffeeScriptCJavaScript

Github contributions (5)

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ajing/BioinfoAlgorithm

Oct 2013 - Jan 2014

Contributions:81 commits in 3 months
ajing/ChemTreeMap

Dec 2013 - Apr 2017

An Interactive Map of Biochemical Similarity in Molecular Datasets. The document: http://chemtreemap.readthedocs.org/en/latest/ . The project website:
Contributions:3 releases, 392 commits, 1 PR in 3 years 4 months
similaritymolecularproject-websitemapdatasets
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