Maxim Kobelev
Summary
Maksim Kobelev is a Senior Data Scientist based in Budapest with 7+ years in machine learning, specializing in NLP, computer vision and document processing, and five years of commercial experience delivering production-grade systems. He has led teams and driven architecture shifts from lightweight NN models to BERT-based and multimodal transformers, enabling few-shot on-premise learning and improved document clustering and extraction accuracy. At EPAM he built a GPU-accelerated, GStreamer-based OCR pipeline deployed to NVIDIA Orin edge devices for real-time package print-defect detection across global factories, and developed LLM-driven anomaly detection for large-scale general ledgers. Known for bridging research and operations, he combines model innovation (e.g., Visual-Transformer features, GCNs for receipts) with pragmatic deployment—Docker, Azure, Ansible—and operator-facing analytics. His background in financial technologies and applied mathematics helps him design robust, auditable ML solutions that reduce manual work and scale across enterprise environments.
5 years of coding experience
Github Skills (3)
bug-tracker5
python3
segmentation2
Programming languages (2)
Github contributions (5)
morph1max/YDeal
Feb 2021 - May 2022
A system of autotests for practical tasks with built-in anti-plagiarism.
Contributions:32 commits, 1 PR, 21 pushes in 1 year 3 months
pythonantipractical-taskspracticalautotests
sheriff1max/web-recs-searcher
Dec 2023 - May 2025
Contributions:1 release, 21 pushes, 2 branches in 1 year 5 months
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