Pauline Nicolas

AI / Machine Learning – Homepage & Recommender Systems I lead a multidisciplinary team of 9 people at leboncoin, focused on personalizing the marketplace experience through machine learning (Deep Learning, GenAI). The team includes front-end and back-end developers, QA analysts, data scientists, and machine learning engineers. Responsibilities: • Define quarterly roadmaps and shape the long-term vision in close collaboration with Product Management • Guide the team’s expertise in machine learning and deep learning to develop scalable, high-impact solutions • Drive project delivery, ensuring alignment with business goals and technical excellence • Implement Agile best practices to optimize workflows and improve team velocity • Organize refinement sessions and workshops to define project specifications and key milestones • Mentor team members, fostering both technical growth and career development Key Achievements: • Co-designed and launched a ML-powered personalized homepage (ad recommendations and dynamic ranking) with the Product Owner, resulting in a 10% increase in leads • Led multiple large-scale technical initiatives, including the deployment of a vector database (Milvus) for real-time similar ad recommendations, the infrastructure migration of the visual search feature, and the scaling of the recommendation system from leboncoin to Kleinanzeigen, expanding reach by 35M users

• Improving and maintaining the homepage recommender system of leboncoin.fr using collaborative filtering methods, recommending content to 15+ million users • Creating a new “more like this” recommendation model by combining multiple data types (text, images, tabular data), as well as a seller recommender engine using deep learning methods • Developing and maintaining Kubeflow pipelines and applying MLOps best practices to automate model training and predictions