Marcin Kusmierski - Machine Learning Engineer at Intel Corporation

Marcin Kusmierski

Machine Learning Engineer at Intel Corporation

Lodz Metropolitan Area Poland

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Summary

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Rockstar

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Top School

Marcin Kusmierski is a Machine Learning Engineer with over 12 years in software development and a focused 6-year track record as a senior technical leader in automotive middleware. He is proficient in C++ (C++11), Python, and cross-platform application development—primarily on Linux—and brings practical experience with CMake, GTest/GMock, and Visual Studio. At Intel he contributes to OpenVINO’s GNA plugin, delivering performance optimizations such as automatic model splitting and fixes for inference accuracy and I/O dimension issues in a widely used open-source AI inference toolkit. He is keen to expand into graphics and computer vision, leveraging his low-level systems background to bridge model deployment and runtime efficiency. Based in the Łódź metropolitan area, he pairs formal software engineering education (M.Sc.) with hands-on open-source impact, signaling an engineer who values robust, production-ready solutions. An under-the-radar strength is his history of refining existing code paths for clarity and efficiency, not just building new features.

3 years of coding experience

VI LO Piotrków Trybunalski

Master of Science (M.Sc.), Computer Science( Software Engineering and Network Systems), Master of Science (M.Sc.), Computer Science( Software Engineering and Network Systems) at Technical University of Lodz,

Polish, English

Github Skills (8)

c-language10

inference10

cprogramming-language10

ai10

openvino10

optimization10

deep-learning9

computer-vision9

Programming languages (1)

C++

Github contributions (5)

openvinotoolkit/openvino

Jul 2022 - Jan 2023

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference

Role in this project:

Back-end Developer & ML Engineer

Contributions:487 reviews, 13 commits, 76 PRs in 6 months

Contributions summary:Marcin primarily contributed to the `openvinotoolkit/openvino` repository by removing unused command-line arguments within sample code, indicating efforts to refine existing code and improve efficiency. They also made significant changes to the GNA plugin, adding automatic model splitting for compiled graphs and fixing accuracy degradation issues. Furthermore, the user worked on addressing inference issues related to input/output dimensions and incorporating PWL approximation improvements. These contributions suggest a focus on performance optimization and enhancement of the GNA plugin for model deployment and execution.

inference-enginepytorchmodel-optimizerdeep-learninggpu

marcinkusm/openvino

Jun 2022 - Sep 2023

OpenVINO™ Toolkit repository

Contributions:290 pushes, 66 branches in 1 year 3 months

pytorchdeep-learninggpuopenvino-toolkitcomputer-vision

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