Gleb Gladilov
AI Frameworks Engineer at Intel Corporation
Dublin, Ireland
Summary
🤩
Rockstar🎓
Top SchoolGleb Gladilov is an AI Frameworks Engineer based in Dublin with nine years of experience optimizing and porting neural networks across Intel architectures (CPU, FPGA, Movidius) and contributing low-level performance work in C/C++, ASM and SIMD. At Intel he has moved from intern to engineer, focusing on inference and VPU backends for OpenVINO where his bug fixes and enhancements improved Myriad plugin memory allocation, dynamic shape handling and native Gather support. He combines systems-level performance tuning (AVX2, Neon) with tooling for validating deep learning accuracy, and has a strong background in HPC, CUDA, MPI and profiling from academic work. Known for pragmatic, debug-friendly changes, he brings deep hardware-aware insight to make production AI inference faster and more reliable.
9 years of coding experience
6 years of employment as a software developer
Master’s Degree, Institute of Information Technology, Mathematics and Mechanics, Diploma with honors, Master’s Degree, Institute of Information Technology, Mathematics and Mechanics, Diploma with honors at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Русский, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
graph10
computer-vision10
c-language10
inference10
deep-learning10
cprogramming-language10
openvino10
ai9
Programming languages (5)
Github contributions (5)
openvinotoolkit/openvino
May 2020 - Jun 2021
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 reviews, 31 commits, 3 PRs in 1 year
Contributions summary:Gleb primarily worked on the inference-engine/src/vpu directory of the OpenVINO toolkit. They focused on bug fixes and enhancements related to the VPU (Vision Processing Unit) backend, particularly for Myriad plugin. Their contributions include addressing memory allocation issues, fixing DTS (Dynamic to Static Shape) transformations, and enabling support for features like dynamic Reshape and native Gather. The user also worked on annotations for stage memory types to aid debugging and performance analysis.
inference-enginepytorchmodel-optimizerdeep-learninggpu
ggladilo/openvino
Sep 2022 - Sep 2024
Contributions:15 pushes, 5 branches, 1 comment in 2 years
pytorchdeep-learninggpuopenvino-toolkitcomputer-vision
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.