About me. I've spent ten years building ML systems end to end, from classical models to multi-agent AI, and leading the teams that ship them.

Experience

1. MacPaw

   • Staff AI EngineerDec 2025 – now
   • AI Product Lead / Lead Data ScientistOct 2024 – Dec 2025
   • Senior Data ScientistAug 2020 – Sep 2024

   Advanced AI/ML solutions for products used by millions of iOS and macOS users: defining ML strategy, leading applied R&D, and developing production-ready machine learning systems across NLP, computer vision, predictive modeling, and privacy-preserving AI.

   • Computer Vision: semantic segmentation, object detection on photos and videos, image classification, and image reconstruction/enhancement (image inpainting).
   • NLP: text classification, metric learning, information extraction and processing, Multi-Agent systems design, RAG pipeline development, and LLM fine-tuning.
   • Predictive Modeling: forecasting customer lifetime value (LTV) and customer churn.
   • Federated Learning: training neural networks for computer vision directly on user devices, improving models while preserving data privacy.

2. State Scientific and Research Institute of Cybersecurity Technologies and Information Protection

   • Machine Learning / AI SpecialistSep 2024 – Present

   Applied AI/ML projects in the defense technology domain, with most details subject to NDA. Work focuses on computer vision, structured data analysis, trajectory prediction, and audio recognition for military-related use cases.

   • Computer Vision: detection and recognition of aerial objects, including UAVs and FPV drones.
   • Trajectory Prediction: analysis of structured sensor data to predict aerial object movement.
   • Audio Recognition: classification of military-related sound sources.
   • Synthetic Data Generation: creation of synthetic datasets to support model training and evaluation.

3. Kyiv School of Economics

   • Academic Director of Artificial IntelligenceMay 2023 – Feb 2024

   Created and launched a Bachelor's program in Artificial Intelligence aligned with modern industry standards, emerging AI trends, and labor market needs. Designed a curriculum combining theoretical foundations with practical AI engineering skills. The program currently has 140 students. I also support collaboration between MacPaw and KSE to strengthen industry-academia connections in the technology sector.

4. FairmarkIt

   • Senior Data Scientist / Team LeadOct 2019 – Mar 2021

   Led development of a comprehensive search solution for platform efficiency in the Supply Chain sector, heading a team of Data Scientists and ML Engineers. Developed a multilingual semantic search algorithm to optimize search across various languages.

   • Deep learning-based search engine with Learning-To-Rank functionality.
   • Domain-specific hierarchical text classification with custom BERT-based models.
   • ML infrastructure on AWS; scalability and reliability through best-practice adoption.

5. Eleks

   • Data ScientistSep 2018 – Sep 2020

   Designed and developed data science solutions for a diverse range of clients across multiple industries.

   • Embedded Systems: optimized neural networks for resource-constrained devices via quantization, pruning, and inference acceleration; built an internal CV framework similar to ONNX.
   • Security: robust object tracking for video surveillance using SORT, DeepSORT, and YOLO-based detectors.
   • Healthcare: semantic segmentation for medical image analysis with U-Net and FCN architectures, supporting clinical decision-making.

6. SoftServe

   • Python Software EngineerFeb 2016 – Sep 2018

   Developed and enhanced a large-scale American e-commerce project, from software design to integrating machine learning technologies.

   • Robust web-scraping systems with asynchronous data retrieval and optimized data pipelines.
   • Python best practices: modular design, unit testing, continuous integration.
   • NLP models automating text data processing, integrated into the existing project ecosystem.

Education

Tools

ML Stack

numpy, scipy, OpenCV, pandas, gensim, nltk, Keras, TensorFlow, PyTorch, CoreML

Databases

MongoDB, PostgreSQL, ElasticSearch, Memsql

Cloud

AWS, Google Cloud

OS

Linux, macOS