Artem Zabolotnyi
Summary
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SeniorArtem Zabolotnyi is a Senior ML Researcher with 9 years of experience combining deep learning research and full-stack engineering, currently driving transformer-based risk modeling at SberBank. He has led development and deployment of large-scale transformer models (10–30+ billion parameters) across clusters of hundreds of GPUs, producing improvements in credit scoring that translated to tens of billions of rubles in financial impact. His background spans CV, NLP, and audio, plus practical expertise in PyTorch, DeepSpeed, MLflow, Hadoop/Spark and production ML pipelines, enabling seamless research-to-production workflows. Earlier full-stack roles gave him hands-on skills in microservices, CI/CD and frontend engineering, so he comfortably bridges model research and service engineering. As a PhD researcher and lecturer at Skoltech he explores uncertainty estimation and efficient transformer designs, and he enjoys mentoring peers and distilling scientific papers into practical architectures. An unassuming detail: he pioneered using large GPU clusters at SberBank and won the 2023 R&D Breakthrough prize for the X-Former project.
9 years of coding experience
Github Skills (2)
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denoising1
Programming languages (2)
Github contributions (5)
zaaabik/face-fecognition
Dec 2018 - Jul 2019
Contributions:21 PRs, 253 pushes, 22 branches in 6 months
zaaabik/AdUE
May 2025 - Oct 2025
Contributions:1 PR, 229 pushes, 1 branch in 4 months
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