The short version.

I build AI systems that spend more time in production than in demos. My work lives at the intersection of computer vision8 yrs, deep learning7 yrs, and the less glamorous engineering that keeps either one actually useful — FastAPI5 yrs services, Docker5 yrs pipelines, plant-floor PLCs, HPC job schedulers. The boring parts. The parts that don't show up in a Medium article.

Most recently I was a data engineer at the University of Pittsburgh, running 10+ production Airflow pipelines and shipping a RAG3 yrs Slack assistant that cut repetitive student support requests by 30%, while facilitating courses for 300+ students. Alongside that, I built a satellite-imagery detection platform for Airoverse. Before Pitt, years in the field: automating fifteen manufacturing facilities and building predictive-maintenance pipelines for HVAC equipment. The full history is in the record.

I hold an M.S. in Information Science (AI specialization) from the University of Pittsburgh. My French Talent Passport Famille visa means I'm work-authorized from day one in Paris. I'm pragmatic, measured, and mildly allergic to ML pitches that won't survive contact with real data.

If you're hiring for a role where the model has to actually ship — on real hardware, to real users, under real budgets — we should probably talk.