Tomasz Bartczak
Senior Software Engineer at Google
Warsaw, Masovian Voivodeship, Poland
Summary
👤
Senior🎓
Top SchoolTomasz Bartczak is a Senior Software Engineer with 12 years of experience specializing in applied machine learning, medical imaging and learning-to-rank systems, currently working at Google after recent roles building clinical segmentation and diagnostic models. He bridges research and production—publishing on context-aware self-attention for ranking, contributing code to Keras to improve distributed training, and shipping large-scale ranking and detection systems that moved real business metrics. Tomasz has deep hands-on expertise in multi-GPU 3D medical model training, deployment on cloud platforms, and integrating ML models into high-throughput services (up to thousands of RPS). He regularly presents at PyData and SIGIR workshops, and brings a pragmatic mix of engineering rigor and research curiosity—evident in open-source work like allRank and Keras contributions that improve distributed training robustness.
12 years of coding experience
16 years of employment as a software developer
Master's degree, Master's degree at Lodz University of Technology
Github Skills (18)
distributed-training10
apidoc10
python10
data-science10
machine-learning10
flask-ask10
keras10
deep-learning10
api10
tensorflow10
neural-network10
flask10
testing9
convolutional-neural-networks9
visualization9
Programming languages (11)
Github contributions (5)
keplr-io/quiver
Nov 2016 - Jul 2017
Interactive convnet features visualization for Keras
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:8 commits, 9 PRs, 23 comments in 7 months
Contributions summary:Tomasz primarily worked on back-end aspects of the project, specifically modifying the server-side code and API endpoints. Key contributions include adding functionality for custom classes and top-n predictions, as well as fixing image path resolution issues. They also integrated ImageNet fallback mechanisms and made modifications to the image loading process. Furthermore, the user contributed to the front-end code by merging branches, specifically modifying Javascript files related to the visualization tool.
deep-learningconvnettensorflowconvolutional-neural-networkskeras
keras-team/keras
Jun 2022 - Aug 2022
Deep Learning for humans
Role in this project:ML Engineer
ML EngineerContributions:5 reviews, 11 commits, 2 PRs in 1 month
Contributions summary:Tomasz primarily contributed to the Keras library by implementing and refining the `distribute_reduction_method` functionality. They introduced the ability to configure how loss and metric values are reduced across replicas, especially for custom training steps and distributed training strategies. This work included adding the "sum" reduction option and providing corresponding tests and documentation updates. The contributions improved the library's capabilities for distributed training and performance monitoring.
pythondata-sciencedeep-learningneural-networksmachine-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.