Dialog AI enhances the online shopping experience by delivering real-time, personalized answers directly on your e-commerce website

• Contributing to Suez CoDAI: an internal MLOps framework centralizing data science projects, from code packaging to ML pipelines and model deployment• Exploring and prototyping LLM-based applications to streamline technical/business teams tasksadapted to heterogeneous proprietary experts data

• Lead cross-team effort to deploy new deep learning recommendation engine on 100+ clients along their migration to code/data production stack on GCP. • Contributed to design and implentation of MLOps tools to accelerate model setup for each client and debug of predictive performance: Configuration Automation, Model explainability, Feature importance/selection, Hyperparameter tuning• Explored, experimented and designed product features based on new predictive engine capabili-ties: ”Semantic” Topic Search - e.g. product, brand, travel destination - using Embeddings, Product Cold Start, Customer Lifetime Value

• Contributed to design and scale of training, evaluation and inference pipelines of in-house deep learning models using KubeFlow and Tensorflow. The custom models were inspired from Deep Factorization Machines, they involved self-supervised learning along with model transfer• Supervised research internship topics: • Leverage offer embeddings - e.g. products, brands, categories - to provide topic similarity measure. Build new representations to embed offer complementarities • UserProfile - socio-demo representation using Self-Supervised learning

Master Thesis: Hierarchical Regularization Techniques for Neural-based Factorization MachineExplored, evaluated and deployed recommender systems based on neural networks

Collaborated on Research project: Deep Reinforcement Learning Applied to Starcraft AI Research EnvironmentNVIDIA AI Technology Center (NVAITC)

Assisted a PhD student on water retention properties of a particular clay in orderto design high-level radioactive waste repositories. The first month was dedicated tolearning Chinese and discovering the Chinese culture through visits of various cities.