Summary
Alexis Benichoux is a research-focused machine learning engineer with eight years of industry experience building recommender systems, content moderation pipelines and medical-imaging ML at companies including Deezer, Believe, Yubo, TheraPanacea and Criteo. He combines a strong academic foundation—a PhD in signal processing and a Master’s in Math/Vision/Learning—with hands-on production work in collaborative filtering, playlist completion, user-to-user recommendations and algorithmic artist discovery. More recently he led ML teams applying deep learning to medical imaging and scaled ML efforts at Criteo before moving into a research engineer role at Gradium. Known for bridging research and product, he has decade‑long roots in signal processing (sparse representations, source separation and tensor methods) that inform robust, theory-driven solutions in production systems. Based in Paris, he brings rare multidisciplinary experience spanning neuroscience fMRI studies to large-scale personalization platforms.
8 years of coding experience
8 years of employment as a software developer
Master 2 (M2), MVA Mathématiques / Vision / Apprentissage, Master 2 (M2), MVA Mathématiques / Vision / Apprentissage at ENS Paris-Saclay
Docteur en traitement du signal et télécommunications, Docteur en traitement du signal et télécommunications at Université de Rennes I
M1 Mathematiques fondamentales et appliquées, M1 Mathematiques fondamentales et appliquées at Paris-Sud University (Paris XI)
MPSI/MP, MPSI/MP at Lycee Henri IV
ENSAE Paris
English