À propos de Maximilien
I build AI Agents and RAG architectures for industry leaders, with a specialization in Healthcare.
With a background at Roche and NVIDIA, I bridge the gap between cutting-edge research and scalable industrial applications. I help companies transform proprietary scientific data into actionable intelligence through autonomous AI agents.
Track Record:
- Roche: Architecting LLM solutions to accelerate the molecular life cycle.
- NVIDIA: Optimizing 3D medical pipelines for real-time surgical use.
- Jengo: Built multi-channel AI Agents as CTO/Lead Engineer.
- MICCAI: 3rd place worldwide at the 2023 3D tumor segmentation challenge.
Why work with me?
- Domain-Specific RAG: Architecting high-precision retrieval pipelines optimized for restricted, proprietary, and scientific datasets.
- Healthcare & BioTech Focus: Proven expertise in handling clinical data, 3D medical imaging, and navigating strict regulatory compliance.
- Production-Grade Infrastructure: Deploying scalable, real-time AI solutions directly to production using AWS or GCP
Technical Tags:
Français
Bilingue ou natif
Anglais
Bilingue ou natif
En télétravail uniquement
Travaille majoritairement à distance
Expériences
- Roche PharmaceuticalsSenior GenAI Engineer & Data ScientistBIOTECHNOLOGIESfévrier 2026 - Aujourd'hui (4 mois)Bâle, SuisseWorking at Europe's biggest pharmaceutical company :- Developing sophisticated LLM-powered solutions to accelerate the molecular life cycle and drug discovery processes.- Architecting complex Agentic Workflows and multi-agent systems using LangGraph to automate advanced reasoning for researchers.- Building high-precision RAG (Retrieval-Augmented Generation) architectures to leverage proprietary scientific data at scale.-Deploying and scaling production-ready AI infrastructures and pipelines on AWS within a highly regulated environment.
- NVIDIAAI Engineer | Computer Vision & Medical ImagingHIGH TECHmai 2023 - août 2024 (1 an et 4 mois)Paris, FranceOptimizing 3D medical imaging pipelines for maxillofacial surgery:-Designing high-fidelity reconstruction pipelines for CBCT, balancing dose exposure with image quality.-Developing Deep Learning algorithms for tomographic reconstruction using Self-Supervision and Generative Energy-Based Priors.-Restoring high-precision 3D volumes from undersampled raw data (sinograms) to enhance diagnostic clarity.-Optimizing real-time performance on NVIDIA hardware, leveraging parallel computing for clinical environments.-Implementing state-of-the-art models to accurately process bone and soft tissue morphology.
- JengoCTO & Lead AI EngineerBANQUE & ASSURANCESjuillet 2024 - août 2025 (1 an et 1 mois)Paris, FranceSteering the technical vision and end-to-end development of an AI-driven SaaS ecosystem :-Deploying a multi-tenant SaaS platform to manage corporate clients and track case statuses in real-time.-Designing a multi-channel AI Agent capable of orchestrating complex, consistent interactions via SMS, Email, and Phone Call.-Implementing NLP pipelines for sentiment analysis and intent extraction to dynamically adapt recovery strategies and tone.-Developing AI-driven business logic for recovery scheduling, payment promise tracking, and early detection of escalation signals.
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Formations
- Diplôme d'ingénieur en informatique & intelligence artificielleEPITA: Ecole d'ingénieurs en informatique2024Ingénieur en informatique et intelligence artificielle
Certifications
- Machine learning in Python with scikit-learn (Inria)Inria & France Université Numérique2024
- React, NodeJS, Express & MongoDB - The MERN Fullstack GuideUdemy2024