Working on ML and Computer Vision solutions for one of the world's most prestigious fast-food chains. Leveraging Databricks for scalable data pipelines and model training.

Taught Data Analytics at the Master's level: EDA, embeddings, dimensionality reduction (PCA, t-SNE, UMAP), and applied ML. Three-hour weekly lectures combining theory and hands-on coding.

Development and deployment of ML models (LLMs, recommendation systems, classifiers). Built a product taxonomy using LLMs that significantly improved search and restaurant/product recommendations — currently live across multiple Delivery Hero markets worldwide. Designed and ran A/B tests and measured recommendation diversity at scale.

Updated and deployed a recommendation system for a major global clothing brand using Neural Networks trained on user activity. Also worked on semantic search and product similarity.

Built a job candidate recommendation system using NLP to extract key skills from resumes. Analyzed social media posts to detect untapped market opportunities.

Backend development for U.S. clients with Ruby on Rails. Delivered scalable, secure solutions using Scrum methodology in cross-functional teams.

Taught Integral Calculus, Linear Algebra, and Symmetry at undergraduate level.