Kyle Xie
Senior Software Engineer at Google
Waterloo, Ontario, Canada
Summary
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Senior🎓
Top SchoolKyle Xie is a Senior Software Engineer with nine years of experience building scalable, distributed systems and production ML/NLP services, currently at Google in Waterloo. He combines strong problem-solving instincts with clear communication, making complex system designs accessible to peers and stakeholders. Past roles include developing large-scale natural language understanding cloud services at RSVP.ai and contributing to reproducible information retrieval research via Anserini—where he added Washington Post collection support and improved indexing utilities. His academic background in computer science and geomatics from Wuhan University and the University of Waterloo informs a pragmatic, data-oriented approach to engineering. Colleagues note his eagerness to learn new technologies and take on challenging integrations that bridge research and production.
8 years of coding experience
5 years of employment as a software developer
Bachelor's Degree Geographic Information Science and Cartography, Bachelor's Degree Geographic Information Science and Cartography at Wuhan UniversityMaster of Mathematics Computer Science, Master of Mathematics Computer Science at University of Waterloo
English, Chinese
Github Skills (8)
lucene10
javas10
information-retrieval10
java10
json8
data-structure7
data-structures7
algorithms6
Programming languages (2)
Github contributions (5)
castorini/anserini
Jun 2018 - Jan 2019
Anserini is a Lucene toolkit for reproducible information retrieval research
Role in this project:
Back-end Developer
Back-end DeveloperContributions:11 commits, 11 PRs, 55 comments in 7 months
Contributions summary:Kyle primarily contributed to the Anserini project by adding support for the Washington Post collection. This involved creating a `WashPostDocument` class to parse Washington Post articles and modifying the `WashPostCollection` class to facilitate indexing. The user also patched the NYT collection indexing, by refactoring the code to directly index `.tgz` files and introduced a utility to dump document vectors from the index.
reproducibleretrievalluceneinformation-retrievaljava
Kytabyte/Anserini
Jun 2018 - Jan 2019
An information retrieval toolkit built on Lucene
Contributions:76 pushes, 4 branches in 7 months
retrievalluceneinformation-retrieval
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