Frank Dai

Staff Software Engineer at Walmart Global Tech

California, United States
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Summary

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Top expert inHigh-Performance Computing and Networking Technologies
Frank Dai is a Staff Software Engineer with 17 years of experience building large-scale data and ML systems, currently improving Walmart.com’s recommendation engine. He is AWS Certified Solutions Architect – Professional and a Cloudera Certified Hadoop developer who has designed production ML serving platforms (Kubeflow) and scalable Spark/Hadoop pipelines across Google, WeRide.ai, and other enterprises. Frank authored crypto-crawler, an open dataset project that accumulated petabytes of market data and powers a coinsignal.org demo, reflecting his appetite for data-at-scale and real-world experimentation. He blends backend, infra, and data engineering—shipping GraphQL backends, Kafka/SQS-driven pipelines, and production Spark optimizations—while often “testing in prod.” Based in California, he pairs deep systems know-how with pragmatic engineering leadership, frequently improving reliability and performance in high-throughput environments.
code17 years of coding experience
job8 years of employment as a software developer
bookBachelor Computer Science, Bachelor Computer Science at Wuhan University
bookDropped out, Dropped out at Tsinghua University
languagesChinese, English
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Stackoverflow

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4,077reputation
2.9mreached
42answers
39questions
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top-5%
apache-spark
top-5%
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Github Skills (25)

reformatting10
apache-spark10
formatting10
big-data10
machine-learning10
text-formatting10
ml10
scala10
latex10
naive-bayes10
text-format10
code-formatting10
java9
layout9
textbox9

Programming languages (17)

JavaC++CRustCMakeTeXScalaGo

Github contributions (5)

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Classical equations and diagrams in machine learning
Role in this project:
userTechnical Writer
Contributions:67 commits, 7 PRs, 10 pushes in 8 years 3 months
Contributions summary:Frank's contributions primarily involve modifications to the `svmult.cls` file, suggesting a focus on customizing the document's layout and formatting within the LaTeX environment. This includes adjustments to page size, margins, and spacing, as well as ensuring proper chapter and section formatting, which likely resulted in improved readability and visual presentation. The user also addressed the display of bold Greek letters.
equationsdiagramsmachine-learning
Contributions:3 releases, 19 commits, 18 pushes in 10 months
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