Artyom Anokhov
AI Frameworks Engineer at Intel Corporation
Munich, Bavaria, Germany
Summary
🤩
Rockstar🎓
Top SchoolArtyom Anokhov is an AI Frameworks Engineer with six years of experience building release engineering, CI/CD and deployment automation for high-performance AI inference tooling. Based in Munich, he has led end-to-end packaging and distribution work for Intel's OpenVINO—creating nightly delivery pipelines, integrating packages into Conda-Forge, Homebrew and a private PyPI, and ensuring cross-platform installs on Linux and macOS. His background blends deep validation and test automation with DevOps: he designed product validation pipelines, deployment managers, and secure internal release pipelines while contributing cross-platform installation automation to the prominent open-source OpenVINO project. Earlier roles in large-scale spam analysis at Mail.Ru cultivated strong data-driven problem solving and systems-level scripting skills (LUA, Python, Hadoop). He’s comfortable shipping both developer-facing packaging infrastructure and the operational tooling that keeps hardware-accelerated ML runtimes reliable in production.
5 years of coding experience
6 years of employment as a software developer
Master's degree, Applied mathematics and computer Science, Master's degree, Applied mathematics and computer Science at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Github Skills (16)
dependency-management10
sh10
automation10
linux10
bash10
automations10
script10
shell10
devops10
deployment-automation10
scripting10
operating-system10
openvino9
ai7
computer-vision6
Programming languages (8)
Github contributions (5)
openvinotoolkit/openvino
May 2020 - Dec 2022
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Role in this project:
DevOps Engineer & Automation Engineer
DevOps Engineer & Automation EngineerContributions:25 releases, 141 reviews, 53 commits in 2 years 6 months
Contributions summary:Artyom primarily contributed to the repository by modifying shell scripts related to the installation and setup of dependencies, particularly for the OpenVINO runtime and its associated drivers. Their work involved updating scripts to download drivers, check versions, and configure the environment, demonstrating an understanding of build and deployment processes. The contributions also included updating installation scripts for different operating systems (Ubuntu, CentOS, RHEL), showcasing skills in cross-platform automation and dependency management. Furthermore, the user integrated new features and updated configurations within the installation process.
inference-enginepytorchmodel-optimizerdeep-learninggpu
artanokhov/openvino
May 2020 - Mar 2025
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
Contributions:137 pushes, 98 branches in 4 years 10 months
pytorchdeep-learningdeploymentopenvino-toolkitobject-detection
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