Mateusz Sluszniak
Software Engineer at Software Mansion
Krakow, Lesser Poland Voivodeship
Summary
🤩
Rockstar🎓
Top SchoolMateusz Sluszniak is a software engineer with six years of experience building cross-platform systems and on-device AI tooling, currently contributing to Huawei’s React Native Harmony OS at Software Mansion. He holds an MSc in Computer Science with honors from AGH University and has a strong competitive-programming and algorithms background that informs his pragmatic, performance-focused approach. Previously he was a core open-source maintainer at Dashbit, implementing ML algorithms in Elixir and contributing notable numerical features to the popular Nx library (e.g., weighted_mean, median, mode, and enhanced SVD handling). Comfortable in C++, Python and Elixir, Mateusz has shipped C++ backends for mobile inpainting apps and automated integrations for large-scale OS projects like Amazon VegaOS. He blends academic rigor with hands-on engineering, and often documents and shares his work through articles and tutorials to help other developers adopt on-device AI.
6 years of coding experience
2 years of employment as a software developer
High School Diploma, High School Diploma at The August Witkowski 5th High SchoolMaster of Science - MSc, Computer Science, Cumulative GPA: 4.84/5.0, Final Grade: 5.0/5.0 with Honors, Master of Science - MSc, Computer Science, Cumulative GPA: 4.84/5.0, Final Grade: 5.0/5.0 with Honors at AGH University of KrakowIndividual programme of study (Physics), Individual programme of study (Physics) at Jagiellonian University
English, Polish, German
Github Skills (6)
tensor10
numerical10
svd10
elixir10
jit7
python4
Programming languages (7)
Github contributions (5)
elixir-nx/nx
Feb 2022 - Jan 2023
Multi-dimensional arrays (tensors) and numerical definitions for Elixir
Role in this project:
Back-end Developer
Back-end DeveloperContributions:39 reviews, 10 commits, 26 PRs in 11 months
Contributions summary:Mateusz contributed to the core functionality of the `nx` library, focusing on numerical operations and tensor manipulation. Their work included adding new features such as `weighted_mean` and `median`, and fixing edge cases in existing functions like `norm`. They also implemented the `mode` function and enhanced the SVD (Singular Value Decomposition) functionality with the `:full_matrices?` option.
pytorchmulti-dimensionalxlajitgpu
msluszniak/scholar
Aug 2022 - Jul 2024
Machine learning tools built on top of Nx
Contributions:2 PRs, 593 pushes, 217 branches in 1 year 11 months
deep-learningneural-networksmachine-learningon-top
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.