Our Core Team

Over the years we have worked with 50+ engineers, researchers, and domain experts across different projects. Here is the core team driving AI Labs today.

AI Labs is a distributed AI engineering team operating across the United Kingdom, Ukraine, and Slovakia. Founded in 2012, we cover a wide range of AI and software engineering domains — from NLP and computer vision to signal processing and agentic AI — because we have dedicated specialists and teams for each discipline, backed by over 14 years of hands-on expertise. The team members listed here represent our core management and technical leadership.

Operating inUnited Kingdom · Ukraine · Slovakia
Clients since 2012Ukraine · United States · United Kingdom · Norway · Israel · Japan · Switzerland · Germany · Poland
Oleksandr Korobov

Oleksandr Korobov

AI/ML Architect · Research Lead

He acts as a technical consultant and AI systems architect, leading the design of advanced machine learning platforms while remaining hands-on in complex engineering work. With over a decade of experience across NLP, computer vision, signal processing, and multimodal AI, he has built large-scale transformer-based systems, LLM and RAG platforms, semantic search engines, and high-load distributed backends in Python.

His expertise includes PyTorch, TensorFlow, Hugging Face, vector databases, cloud-native deployment, and agentic AI systems orchestrating secure, long-running analytical workflows. He also designs and delivers AI/ML and programming courses for MBA programs, universities, software schools, and individual mentoring, combining research depth with production-focused engineering.

Taras Volianskyi

Taras Volianskyi

Data Science Engineer · AI Systems Developer

Acts as a consulting data science engineer, joining project teams where his expertise is needed, while also driving independent work in areas he finds compelling — LLM agents, automation, and analytical systems. Combines strong mathematical intuition with practical engineering. Experienced with transformer-based NLP models (BERT, SBERT, zero-shot learning), predictive modeling, ML-driven traffic analysis, and advertising optimization.

Vlad Cheryachukin

Vlad Cheryachukin

Software Engineer · Backend Developer

Experienced software engineer and backend developer with strong expertise in high-load systems, security, and network architecture. Specializes in scalable RESTful services, asynchronous Python, PostgreSQL, MongoDB, Docker, and cloud platforms. Also contributes to ML infrastructure — distributed pipelines, containerized computation, secure sandboxed execution, and MLOps. Has worked on LLM-based document processing, multimodal AI pipelines, traffic analytics, and medical cloud platforms.

Prof. Dr. Oleksii Sheremet

Prof. Dr. Oleksii Sheremet

Senior AI/ML Engineer · Research Scientist

Provides senior-level consulting on AI architecture and research methodology, and joins projects requiring deep scientific rigour. Pursues independent research driven by his academic interests — computational intelligence, control theory, and physics-informed ML. Doctor of Technical Sciences with a background in dynamical systems and automation. Has designed advanced AI pipelines spanning computer vision, NLP, RAG, and document intelligence. Publishes peer-reviewed work and supervises graduate research.

Ruslan Dynshchyk

Ruslan Dynshchyk

ML & Algorithms Engineer · Data Systems

Machine learning and algorithms engineer with strong foundations in dynamic systems, signal processing, and advanced data analytics. Specializes in tabular data processing at scale, transformer-based systems, and agent-driven workflows for automated data exploration. Background in dynamic systems and signal processing bridges classical algorithmic approaches with modern deep learning. Has contributed to energy domain analytics, predictive modeling, and time-series analysis. Strong in algorithm design, optimization, and ML system visualization.

Lera Cherna

Lera Cherna

Cybersecurity Engineer · QA Lead

Cybersecurity-focused software engineer with a medical background and strong expertise in quality assurance. Experienced in both manual and automated testing, including QA strategies for AI-driven systems, backend services, and data-intensive platforms. Has led QA efforts coordinating multiple testers with structured reporting and production-grade stability standards. Brings heightened awareness of data protection, system integrity, and compliance from working in medical and regulated environments.