Artem Oboturov - SWE L4 at Google

Artem Oboturov

SWE L4 at Google

Zurich, Zurich, Switzerland

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Summary

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Senior

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Top School

Artem Oboturov is a seasoned SWE with 13 years of experience, currently at Google (SWE L4) in Zurich, where he has driven large-scale code migrations and data-quality initiatives for Shopping. He built an AST-based changes framework that automated refactorings across 100k+ configuration files and became a top-100 Google code contributor within six months, evidencing strong automation and large-codebase expertise. His background spans backend systems, search and trading-floor applications, and production ML/document-extraction tooling—he contributed stability and parsing improvements to the notable Grobid project. Artem combines rigorous academic training in databases, data mining and financial mathematics with practical ML exposure (MLSS Kyoto) to bridge research and production. He’s pragmatic about reliability and scalability, repeatedly unblocking migrations and quality bottlenecks. Based in Zurich, he pairs deep engineering craft with a history of shipping mission-critical, high-throughput systems.

13 years of coding experience

6 years of employment as a software developer

BTech Computer Engineering, BTech Computer Engineering at Novosibirsk State Technical University (NSTU)

Master of Engineering Databases and Data mining, Master of Engineering Databases and Data mining at Télécom Paris

Master's degree (ex DEA LAURE ELIE) Financial Mathematics, Master's degree (ex DEA LAURE ELIE) Financial Mathematics at Université Paris Cité

Machine Learning Summer School MLSS 2015 Machine Learning, Machine Learning Summer School MLSS 2015 Machine Learning at Kyoto University

English, French, Russian, German

Stackoverflow

Stats

4,384reputation

735kreached

104answers

36questions

Github Skills (19)

java10

javas10

text-processing10

nlp10

machine-learning9

cookie9

full-text-search9

syntax6

gherkin6

dom-events6

google-chrome6

cucumber6

cors6

javascript6

specflow6

Programming languages (13)

JavaC++CCMakeScalaGoMustacheHTML

Github contributions (5)

kermitt2/grobid

May 2017 - Aug 2017

A machine learning software for extracting information from scholarly documents

Role in this project:

Back-end Developer

Contributions:10 commits, 12 PRs, 17 comments in 3 months

Contributions summary:Artem primarily focused on improving the Grobid project's accuracy and stability. Their commits addressed date parsing ambiguities in the `DateParser.java` file and fixed a language detection issue related to 'zh-tw'. The user also addressed resource leaks in `GrobidRestProcessFiles.java` and improved code related to language-specific text analysis within `GrobidAnalyzer.java`. Furthermore, the user made corrections to the `ReferenceSegmenterParser` for better parsing accuracy and refactored code for text normalization.

pdfdeep-learningfulltextmachine-learningscientific-articles

aoboturov/tp-twitter-hadoop

Oct 2012 - Mar 2013

Contributions:94 commits in 5 months

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