Ondřej Švec
Senior Software Engineer (Team Lead) at Google
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolOndřej Švec is a Senior Software Engineer and team lead based in Zurich with 13 years building bespoke web applications and a strong ML research background from a Masters in Artificial Intelligence at Charles University. He leads a Retail Ads team at Google, improving advertiser onboarding and retention for millions of users, and previously designed advertiser-facing features and APIs for Smart Shopping and Performance Max. Earlier research work at Avast produced a co-authored paper on training deep nets on raw binaries for malware detection, and he has contributed to open-source metric learning tooling by refactoring and hardening algorithms in the widely used metric-learn library. Comfortable spanning from front-end React builds for corporate sites to production ML systems, he combines pragmatic engineering with a researcher's attention to metrics and code clarity. Colleagues describe him as a hands-on leader who still pushes meaningful code improvements while scaling product impact.
13 years of coding experience
15 years of employment as a software developer
Bachelors, Computer and Information Sciences, General, Bachelors, Computer and Information Sciences, General at Charles University in Prague, Faculty of Mathematics and PhysicsMaturita, Obecné gymnázium, Maturita, Obecné gymnázium at Grammar School Uherské Hradiště
Czech, English, French, Chinese, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
scikit10
metric-learning10
machine-learning10
refactoring10
python10
scikit-learn10
algorithms9
implement9
algorithm9
Programming languages (4)
Github contributions (5)
scikit-learn-contrib/metric-learn
May 2016 - Jan 2017
Metric learning algorithms in Python
Role in this project:
ML Engineer
ML EngineerContributions:13 commits, 6 PRs, 11 comments in 8 months
Contributions summary:Ondřej's contributions primarily involve refactoring and enhancing the metric learning algorithms within the `metric-learn` library. They moved parameters into dictionaries for methods like NCA, LFDA, ITML, SDML and LSML, improving code organization and readability. They fixed minor indentation issues and added comments to improve code clarity. The user also added the `__repr__` method to the `BaseMetricLearner` class, and included updates to include fit_constraints methods.
pythonmetric-learningmachine-learninglearning-algorithmsscikit-learn
svecon/web-utilities
Sep 2012 - Nov 2012
Contributions:32 commits in 2 months
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