• Developed ML and DL anomaly detection models applied to filling machines' data, and deployed them both on-edge and on-cloud

• Worked on a self-hosted RAG architecture for internal use

• Member of an AI teaching group to educate employees on both theoretical foundations and practical implementations of AI, covering topics from Machine Learning basics to advanced Generative AI techniques

Front-end software development

Internship for Master thesis. After a period of literature research, I developed a self-supervised, image-based system for anomaly detection and process control in an industrial environment.

In these three years I worked in the Formula Sae team as a developer, with a focus in perception techniques for a self-driving kart, working with Lidars and cameras.