Piotr Szmelczynski
Data Engineer
Gdansk Metropolitan Area Poland
Summary
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Rockstar🎓
Top SchoolPiotr Szmelczynski is a Data Engineering Tech Lead based in the Gdansk Metropolitan Area with five years of experience building and scaling data solutions across startups and enterprise teams. He progressed from machine learning engineering at Intel to hands-on data engineering roles at resonanz, Adastra Digital, and Fetcherr, where he now leads the data engineering function. Piotr combines practical ML inference knowledge with strong test automation chops, having contributed to OpenVINO’s test suites and improved coverage for quantization and core ops like Softmax and MaxPool. He excels at refactoring legacy tests and turning fragile pipelines into reliable, production-ready data workflows. Comfortable bridging research-grade tooling and production constraints, he brings a developer-first approach to data quality and operationalization. Fluent in Polish and grounded in a Computer Science degree from the University of Gdansk, he often surfaces subtle edge-case bugs before they reach production.
5 years of coding experience
4 years of employment as a software developer
Bachelor's degree Informatyka, Bachelor's degree Informatyka at University of Gdansk
Stackoverflow
1reputation
0reached
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Github Skills (8)
graph10
c-language10
cprogramming-language10
test-automation10
testing10
deep-learning9
computer-vision8
ai7
Programming languages (1)
Github contributions (5)
openvinotoolkit/openvino
Sep 2020 - Dec 2021
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:98 reviews, 40 commits, 46 PRs in 1 year 3 months
Contributions summary:Piotr primarily contributed to refactoring and enhancing existing test suites within the OpenVINO™ toolkit. Their work focused on modifying tests related to quantization/dequantization and adding new tests for operations like Tile, HardSigmoid, Softmax, and MaxPool. They also addressed bugs and improved test coverage across various components. The user demonstrates familiarity with the project's testing infrastructure and the underlying computational graph operations.
inference-enginepytorchmodel-optimizerdeep-learninggpu
pszmel/openvino
Sep 2020 - May 2022
OpenVINO™ Toolkit repository
Contributions:1 PR, 323 pushes, 50 branches in 1 year 8 months
pytorchdeep-learninggpuopenvino-toolkitcomputer-vision
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