AI/ML Engineer with hands-on experience in machine learning, computer vision and LLM-based systems. Building end-to-end AI applications using Python, PyTorch and LangChain. Background in deep learning, Transformers, CNNs and software engineering.
- Research: CNN/Transformer pipelines for image denoising and super-resolution (LuminaVision)
- Hackathons: BitNBuild international winner · HackNation 2025 1st place · HackCarpathia 2025 AI winner
CNNs · Transformers · LLMs · AI Agents · Object Detection · YOLO · Segmentation · Super-Resolution · NLP · Classical ML · Deep Learning
Building production-grade automation workflows and agentic systems using:
- n8n - custom nodes, multi-step LLM pipelines, API orchestration and automated reporting workflows
- Make (Integromat) - no-code/low-code integration workflows connecting external APIs, databases and AI services
- AI Coding Agents - working with Claude Code, OpenAI Codex and similar agentic coding tools for accelerated development, code review automation and context-aware refactoring
- LLM API integration - Gemini, GPT, Claude, local models (Ollama) wired into custom agent pipelines with tool use, memory and retrieval
| Project | Description | Stack |
|---|---|---|
| LuminaVision | CNN & Transformer pipelines for image denoising, super-resolution and enhancement | PyTorch, OpenCV, Django |
| RAGBasedAIAssistant | LLM app with RAG pipelines, prompt engineering and AI agent workflows | LangChain, GPT, embeddings |
| ComputerVisionAndAIImageProcessing | Object detection, segmentation, neural image transformations | PyTorch, OpenCV, YOLO |
| Autopocket | AutoML framework for predictive analytics and financial forecasting | Scikit-learn, XGBoost |
