Maksim Kutakov
AI Frameworks Engineer at Intel Corporation
Munich, Bavaria, Germany
Summary
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Rockstar🎓
Top SchoolMaksim Kutakov is an AI Frameworks Engineer with nine years of experience building high-performance, compute‑intensive systems across AI inference and scientific simulation. Based in Munich, he leads CPU plug-in architecture and low-level optimization efforts for OpenVINO at Intel, combining hands‑on C++ and Python development with performance profiling and cross-team technical leadership. His background in aerospace engineering and FEM/rotordynamics gives him uncommon depth in numerical methods, ODE/PDE solvers and physical simulation, which he leverages to optimize deep learning primitives. An active contributor to the widely used openvino project, he has strengthened its testing framework and fixed CPU performance regressions, demonstrating both system-level vision and meticulous engineering.
9 years of coding experience
8 years of employment as a software developer
Engineer's degree, Aerospace, Aeronautical and Astronautical Engineering, Engineer's degree, Aerospace, Aeronautical and Astronautical Engineering at Moscow Aviation Institute (National Research University)
English, Russian, German
Github Skills (11)
inference-engine10
c-language10
cprogramming-language10
openvino10
functional-testing10
test-automation10
unit-testing9
ai7
computer-vision7
deeplearning-ai7
deep-learning7
Programming languages (5)
Github contributions (5)
openvinotoolkit/openvino
Aug 2020 - Dec 2022
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:1872 reviews, 52 commits, 386 PRs in 2 years 4 months
Contributions summary:Maksim primarily contributed to the testing framework within the OpenVINO toolkit. Their work focused on adding and modifying tests for specific functionalities, such as Reverse Seq and GatherTree layers, along with fixes to the existing Reduce operation tests. They also addressed performance-related issues in the CPU plugin. The user demonstrated strong skills in developing functional tests and understanding the underlying architecture of the OpenVINO toolkit by creating new tests for various layers in the inference engine.
aiinferenceopenvinodeep-learningcomputer-vision
maxnick/openvino
Aug 2020 - Jun 2026
OpenVINO™ Toolkit repository
Contributions:68 reviews, 16 PRs, 786 pushes in 5 years 10 months
openvino
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