Janusz Lisiecki
Director, Deep Learning, Site Leader NVIDIA Poland
Warsaw, Masovian Voivodeship, Poland
Summary
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Rockstar🎓
Top SchoolJanusz Lisiecki is a deep learning leader and engineering director at NVIDIA Poland with eight years of focused experience building high-performance data processing for AI workloads. He leads the DALI project team in Warsaw, contributing to world-record deep learning training throughput while steering roadmap, customer engagement, and cross-functional engineering. Janusz combines hands-on systems and firmware expertise from a long tenure at Samsung with strategic open-source stewardship, notably improving DALI documentation and user experience for a widely adopted GPU-accelerated library. Known for scaling teams and shipping production-grade tooling, he brings an uncommon mix of low-level optimization experience (vectorization, DSPs, drivers) and applied deep learning infrastructure. Based in Warsaw, he holds an MSc in Electronics and Computer Engineering and enjoys tackling problems “no one has done before.”
7 years of coding experience
13 years of employment as a software developer
MSc Electronics and Computer Engineering, MSc Electronics and Computer Engineering at Warsaw University of TechnologyMatura Mathematics and Physics, Matura Mathematics and Physics at XXI LO Hugona Kołłątaja w Warszawie
Github Skills (6)
documentation10
user-interface6
interface-design6
ui-design6
pytorch4
tensorflow4
Programming languages (8)
Github contributions (5)
NVIDIA/DALI
Jun 2018 - Jan 2023
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Role in this project:
Technical Writer
Technical WriterContributions:19 releases, 4987 reviews, 944 commits in 4 years 7 months
Contributions summary:Janusz contributed to the documentation of the NVIDIA DALI project, focusing on advanced topics and providing examples for users. They updated the build instructions, added links to relevant resources, and clarified operator argument descriptions. They also added a note on the appropriate use of DALI and incorporated a FAQ section into the documentation, showcasing skills in technical writing and user experience design.
pythontrainingpaddlegpu-accelerationbuilding-blocks
JanuszL/DALI_extra
Apr 2019 - Sep 2023
Test data for DALI project
Contributions:20 pushes, 41 branches in 4 years 6 months
dalitest-data
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