About Me

I am an Applied AI Engineer focused on building real-world intelligent systems using Large Language Models, multimodal AI and modern deep learning techniques.

My work centers around designing and developing production-ready AI applications such as multi-agent research systems, domain-specific fine-tuned language models and computer vision pipelines for practical use cases. I enjoy solving complex problems by combining strong engineering fundamentals with modern AI capabilities.

I actively work across the full AI product stack — from data preparation and model experimentation to backend API development, system design, performance optimization and deployment. My goal is not just to train models, but to build complete AI systems that can be reliably used by real users.

Currently, I am deeply exploring areas such as LLM architecture, tokenization strategies, efficient fine-tuning methods (like LoRA/QLoRA), agent orchestration frameworks, retrieval-augmented generation systems and scalable AI infrastructure.

I am particularly interested in Applied AI and Generative AI roles where I can contribute to building impactful AI products, work on challenging real-world problems and continuously push my understanding of intelligent systems.