Michal Tyrolski
Senior AI Consultant IV at EY
Warsaw, Masovian Voivodeship, Poland
Summary
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RockstarMichal Tyrolski is a Senior AI Consultant with nine years of hands-on experience building and researching deep learning systems, currently based in Warsaw and working at EY. He combines industry consulting with active community leadership at ML in PL, where he has shaped conference programs since 2020. His research and engineering background includes internships and research roles at NVIDIA and Microsoft, Deepflare work on applied DL, and tangible open-source contributions to Google's Trax—implementing core Funnel Transformer components and improving model layers and configs. Known for bridging clean, production-ready code with scientific rigor, he brings both practical deployment experience and conference-level thought leadership to AI projects. An uncommon strength is his track record of moving between research, teaching, and large-scale engineering roles, enabling him to translate cutting-edge models into real-world outcomes.
9 years of coding experience
4 years of employment as a software developer
Github Skills (8)
transformer-models10
machine-learning10
deep-learning10
jax10
tensorflow10
python10
numpy9
deep-reinforcement-learning3
Programming languages (10)
Github contributions (5)
google/trax
Oct 2020 - Aug 2021
Trax — Deep Learning with Clear Code and Speed
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 2 PRs, 6 comments in 9 months
Contributions summary:Michal contributed to the development of the Funnel Transformer model, implementing core components such as `FunnelBlock` and `FunnelEncoder`. They modified the `trax/models/__init__.py` file to incorporate the `_FunnelEncoder` model. Further contributions involved fixing docstrings and modifying the `Parallel` layer in `trax/layers/combinators.py`. Additional commits included adding configuration files for scientific papers and the CIFAR10 dataset related to Relformer models.
pytorchspeeddeep-learningnumpyreinforcement-learning
Vatican-X-Formers/cluster-toolkit
Nov 2020 - Sep 2021
Toolkit for deploying experiments on a cluster.
Contributions:2 reviews, 61 PRs, 73 pushes in 9 months
deployingclusterkubernetes
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