Versailles, Île-de-France, France
AI Office: Go-To-Market (GTM) Strategy Lead (Manufacturing, Automotive, A&D) • As a core member of the AI Office, I lead the Go-To-Market (GTM) strategy for the Manufacturing, Automotive, and Aerospace & Defense industries. • Developed and packaged new Generative AI service offerings, centralizing technical assets to create compelling, market-ready solutions. • Spearheaded responses to major RFPs (Request for Proposals), successfully articulating Capgemini's value proposition to secure strategic partnerships. Client Engagement & Solution Architecture • Architected and delivered end-to-end Generative AI solutions for enterprise clients across diverse sectors, including Telco, Manufacturing, Automotive, Financial Services, and Aerospace & Defense. • Led strategic business framing workshops to identify client needs, define high-impact use cases, and design solutions that deliver measurable business value and ROI. • Oversaw the complete project lifecycle, from technical architecture design to delivery management, while steering the commercial relationship to ensure client success and expansion.
GCP Generative AI Lead, I&D France • 🚀 Lead and mentor a community of 20+ Data Scientists and Engineers, fostering a culture of technical excellence and knowledge sharing on cutting-edge Generative AI projects. • 🛡️ Established and directed a working group on Trustworthy AI, defining best practices and frameworks to address the security, ethics, bias, and privacy challenges of Generative AI. Capgemini & Google Cloud Generative AI Center of Excellence • ☁️ Leveraged privileged, early access to Google Cloud technologies (Trusted Tester Program) to prototype and implement the most innovative GenAI features for our clients. • 🌍 Orchestrated a worldwide Generative AI hackathon for the Capgemini Group, training 8,000+ employees and mobilizing 150 teams to develop innovative solutions in two weeks.
In charge of a C++ CPU / GPU numerical simulation code: • Establish roadmaps • Follow-up and support for developers • Recruitment and internship supervision
Within a team of about twenty research engineers in charge of the development of a massively parallel multi-physics C++ numerical simulation code: • Survey, development and validation of numerical models (mixed-cells, plasma interpenetration) • CPU optimization • Participation in international scientific conferences
Identify markets and develop innovative solutions to optimize processes, create value with data, etc. Here are a few examples: - Daily analysis of the french Trade and Companies Register (>10M companies, >1B data) for automatic detection of non-compliant mentions : • Extract, Load and Transform data from multiple datasets, data cleaning • Highly parallel algorithms for data analysis, flow forecast based on AI (CNN, LSTM) • Data visualization - Machine learning algorithms for medical image classification (Convolutional Neural Network) • Data cleaning (Seaborn, TSNE, …) • Cross-validation, transfer learning, data augmentation • Optimization and analysis - Business driving software • Backend : flow forecast based on statistical methods and AI (CNN, LSTM), dynamic programming for schedule optimization • Frontend : intuitive dashboards to improve decision making
Tierce Maintenance Applicative of APOLLO2 et TRIPOLI4 codes - configuration management - user support - non regression testing
Reduced models and numerical methods for kinetic equations applied to photon transport - Model reduction (Kompaneets equation for Compton scattering, non-equilibrium regime for Doppler effects) - Derivation of moments models (M1 and P1) for the anisotropic Kompaneets equations) - Design of well-balanced and asymptotic preserving numerical schemes for photon transport