Adrian Zuber
Software Engineer at Marketer
Krakow, Lesser Poland Voivodeship
Summary
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Rockstar🎓
Top SchoolAdrian Zuber is a software engineer based in Krakow with 8 years of experience specializing in ML engineering, MLOps, and developer tooling. He has transitioned from data analyst and data scientist roles at mBank, ING, and Grand Parade to building production ML systems at Marketer, bringing both analytical rigor and engineering discipline. An active open-source contributor, he implemented a Weights & Biases callback for Optuna, bridging hyperparameter optimization with experiment tracking in a widely used framework. Adrian combines hands-on backend development with practical ML deployment skills, and his public GitHub reflects a focus on making ML workflows more reproducible and observable.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Bachelor's degree at Uniwersytet Ekonomiczny w Katowicach
Github Skills (7)
hyperparameter-optimization10
python10
machine-learning9
api8
api-design8
integrations8
distribute8
Programming languages (5)
Github contributions (5)
optuna/optuna
Jul 2021 - Nov 2022
A hyperparameter optimization framework
Role in this project:
Back-end Developer
Back-end DeveloperContributions:229 reviews, 350 commits, 57 PRs in 1 year 4 months
Contributions summary:Adrian implemented a Weights & Biases callback within the Optuna hyperparameter optimization framework, enabling integration with the Weights & Biases UI. This involved creating a callback class, adding the callback to the module scope, extending dependencies with the Weights & Biases library, documenting the callback with an example, and marking it as experimental. Furthermore, the user reworked the callback initialization and added attributes to be logged, allowing users to specify the Weights & Biases execution mode.
hyperparameter-optimizationpythonmachine-learningparalleldistributed
xadrianzetx/mobileunet-tensorflow
Aug 2019 - Sep 2020
Lane segmentation model trained with tensorflow implementation MobileNetV2 based U-Net
Contributions:135 commits, 17 PRs, 76 pushes in 1 year 1 month
segmentationtensorflowdeep-learningmobilenet-v2semantic-segmentation
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