Michal Marcinkiewicz
Engineering Manager at NVIDIA
Warsaw, Masovian Voivodeship, Poland
Summary
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Rockstar🎓
Top SchoolMichal Marcinkiewicz is an engineering manager at NVIDIA with seven years of experience transitioning deep learning research into production-grade systems. He holds a PhD in Physics from the University of Montpellier and began his career in research and internships across Polish and UK institutions before moving into industry roles focused on applied ML. At NVIDIA he advanced from Senior Deep Learning Engineer to manager, contributing to high-profile open-source projects such as NVIDIA/DeepLearningExamples—most notably early RoseTTAFold integrations for protein structure prediction. Michal blends rigorous academic training with hands-on model implementation and loss-function tuning across TensorFlow and PyTorch stacks. Based in Warsaw, he’s known for guiding cross-functional teams to deliver reproducible, enterprise-scale AI workloads while retaining a researcher’s attention to experimental detail.
7 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of MontpellierMaster of Science Physics, Master of Science Physics at University of Warsaw
Italian, French, Spanish, English, Polish
Github Skills (7)
pytorch10
machine-learning10
deep-learning10
tensorflow10
large-language-models9
computer-vision8
nlp7
Programming languages (6)
Github contributions (5)
NVIDIA/DeepLearningExamples
Apr 2020 - Dec 2022
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 11 commits, 4 PRs in 2 years 8 months
Contributions summary:Michal made several commits related to the RoseTTAFold model within the repository, indicating work on a deep learning model for protein structure prediction. Contributions included initial release of RoseTTAFold with related files. The user also modified code related to TensorFlow and UNet, switching between binary_crossentropy and softmax_cross_entropy_with_logits in the losses.py file.
forecastingcaffe2translationspeech-recognitionstate-of-the-art
mmarcinkiewicz/logging
Jan 2021 - Mar 2025
MLPerf logging library
Contributions:3 PRs, 30 pushes, 7 branches in 4 years 3 months
loggermlperflogginglogging-library
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