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Senior Software Engineer | Computer Vision, Deep Learning, AI
Results-driven Senior Software Engineer with over 10 years of experience in software engineering - More than 7 years specializing in computer vision Expertise in developing high-precision computer vision systems for: - Autonomous robots - Industrial safety solutions - Retail analytics Skilled in designing and implementing machine learning models using: - Python - PyTorch - inference speed-up technics - neural network accelerators - C++ Strong emphasis on creating innovative and scalable computer vision solutions Passionate about advancing the field of computer vision Dedicated to leveraging cutting-edge technologies to solve complex problems and drive technological innovation
Taras Shevchenko National University of Kyiv
Master's degree, Radiophysics
January 1, 2007 – January 1, 2013
Lutso
Founding Engineer
April 1, 2025 – June 1, 2026
Tallinn, Harjumaa, Estonia
Starship Technologies
Senior Software Engineer
May 1, 2021 – March 1, 2025
Tallinn, Harjumaa, Estonia
Everguard.ai
Senior Computer Vision Engineer
April 1, 2020 – April 1, 2021
DSIRF GmbH
Data Scientist (Computer Vision)
February 1, 2018 – March 1, 2020
Kyiv
NDA
Machine Learning Engineer
February 1, 2016 – January 1, 2018
Kyiv
Intro Pro
Software Developer
October 1, 2015 – February 1, 2016
Kyiv
Samsung Ukraine R&D Center
Software Engineer
October 1, 2013 – September 1, 2015
Kyiv
2nd International Summer School on Deep Learning 2018
University of Genova
June 24, 2026 – Present
mlcourse_open
OpenDataScience [ods.ai]
June 24, 2026 – Present
Introduction to machine learning by Higher School of Economics
Coursera Course Certificates
June 24, 2026 – Present
Machine Learning by Stanford University
Coursera Course Certificates
June 24, 2026 – Present
Algorithms: Design and Analysis, Part 1
Coursera
June 24, 2026 – Present
Cryptography I
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a broad range of experience across different industries (robotics, industrial safety, retail, blockchain, IoT) and company stages (startup, established R&D). This diversity suggests adaptability and a willingness to tackle varied challenges, which generally indicates a good cultural fit for dynamic and innovative environments. The continuous learning indicated by multiple certifications also points to a proactive and growth-oriented mindset. The target role of ML Engineer aligns well with the candidate's career trajectory and specialized skills.
Soft Skills & Operational Fit
The candidate's resume highlights 'Communication' and 'Problem Solving' as skills across multiple roles. The descriptions of past roles indicate experience in applying technical skills to solve real-world problems in diverse domains like autonomous vehicles, industrial safety, and retail. However, without specific assessment data for soft skills or psychometric tests, a detailed operational fit analysis is limited. The experience as a 'Founding Engineer' suggests an entrepreneurial mindset and ability to work in dynamic environments.