Pol QUIMERC'H.
Work-study Master's student, I build Machine Learning systems with concrete, measurable impact.
Full-stack developer turned AI engineer. I hold a professional bachelor's degree and am now specialising in Machine Learning and Deep Learning through a work-study Master's (RNCP level 7) at EPSI, alongside three years as a data / ML apprentice at Eureden, an agricultural cooperative.
My focus: applied AI with a bias for engineering rigour, from data exploration all the way to reliable production. I am looking for a permanent position in Lyon, France, in R&D, Data Science or ML engineering, available from October 2026.
End-to-end MLOps, open source: from notebook to a FastAPI service on AWS, with automated retraining, drift detection (PSI) and monitoring (Prometheus).
Industrialisation of a critical manual process at Eureden: a serverless data pipeline (AWS Lambda, S3) projecting volumes over a rolling 36 months, with scenario simulation.
Enriching XGBoost yield models with a Sentinel-2 pipeline built from scratch (STAC, COG partial reads, NDVI/EVI/NDWI), plus an ablation study to quantify the gain.
Full case studies, with charts and production screenshots, are on the French projects page.
Prefer to ask directly? The assistant at the bottom right answers in English, about my background, projects or the role I am after.