I’m Giorgos Zachariadis, a results-driven Machine Learning & AI Engineer with over 2 years of experience designing and developing data-driven systems across a variety of industries, including Agronomy, Electrical Energy Management, and Biomedicine.

My work combines practical engineering with a strong research foundation. During my academic career, I focused on Medical Image Captioning, applying advanced deep learning architectures such as CNNs, Transformers, BERT-based models, and RNNs. As the lead for the Caption Prediction Task in the ImageCLEFmedical 2022 competition, my systems achieved 1st and 2nd place rankings out of 10 international teams — with this work published in the CLEF 2022 proceedings. [publication]

Professionally, I have extensive experience solving complex problems using artificial intelligence, machine learning, and natural language processing. I’ve developed and deployed models using frameworks like PyTorch, TensorFlow, and scikit-learn, and have engineered advanced chatbot solutions leveraging NLP and LLM/Generative AI technologies.

In addition to AI, I bring solid expertise in software development with Python and Java, always adhering to clean architecture principles, design patterns, and best practices to deliver scalable, maintainable, and reliable systems. My work spans product development, statistical analysis, and cloud-native deployments using Microsoft Azure and Azure DevOps.

I also have hands-on experience with modern development tools and platforms, including Docker for containerization, FastAPI and Django for REST APIs development, and SQL for efficient data management — all executed with a focus on code clarity, robustness, and software craftsmanship.