À propos de Vincent
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Capacité professionnelle complète
Expériences
- SanofiSenior Machine Learning EngineerSANTÉ & BIEN-ÊTREjuillet 2025 - Aujourd'hui (11 mois)Paris, FranceWorked on applied ML and GenAI products turning large volumes of unstructured enterprise data into usable, AI-powered experiences at Sanofi GenAI team:- Designed and built an end-to-end unstructured data pipeline for documents (PDF, DOCX, XLSX, PPTX, etc.)- Developed multi-stage processing including content extraction, dynamic metadata generation, semantic vectorization, and indexing into vector databases- Applied LLMs and VLMs to enrich, structure, and make enterprise documents queryable at scale- Delivered systems running on AWS and processing millions of documents- Built reusable GenAI agent templates using AWS Bedrock for internal product teams- Developed and deployed multiple production agents (e.g. Confluence assistants, research publication discovery and analysis via APIs)- Implemented evaluation tools for agents using Weave- Worked closely with product, research, and platform teams to turn ML capabilities into concrete internal products
- ProseHead of AIMODE & COSMÉTIQUESnovembre 2024 - juin 2025 (7 mois)Paris, FranceLed the AI team powering Prose’s core personalization engine across haircare and skincare:- Maintained and improved ultra-personalized formula computation, generating near-unique products for each customer- Updated large-scale product recommendation systems- Operated systems handling hundreds of thousands of AI-driven requests per day- Defined AI roadmap aligned with a ~$200M/year revenue business- Drove A/B testing, analytics, and data-informed product decisions- Increased team velocity through simplification, tooling, and process improvements- Acted as an internal AI evangelist, working closely with Product, Tech, and Business teams- Partnered directly with C-level executives through regular 1:1s and leadership forums
- CHANELSenior Machine Learning EngineerLUXEoctobre 2022 - novembre 2024 (2 ans et 1 mois)Member of the Connected Experience Lab, creating memorable digital experiences:- Creation of in-house fiducial tag and real-time decoding algorithm; deployment in web browser (Javascript/TensorflowJS)- Instance segmentation and depth estimation based experience with Pytorch using SOTA models (e.g. SAM, ControlNet...), hybrid deployment on edge and cloud- Development of LLM-based internal training app for beauty consultants
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Formations
- Master de PhysiqueUniversité Paris Sud 112011
- Doctorat de PhysiqueUniversité Paris Sud 112014
Certifications
- Machine LearningCoursera2016
- Deep Learning SpecializationCoursera2017