About

My background is in computer science engineering and machine learning (UTC — Sorbonne Alliance), applied across advertising, logistics, automotive manufacturing and research. Since graduating I've focused on production ML: taking models from notebook to monitored, cost-controlled services.

At Amazon I built ETLs and evaluation APIs for European delivery operations. At BMW I architected a weakly-supervised anomaly detection system for supply chain irregularities and the full MLOps path around it — training, registry, monitoring, APIs and CI/CD. At Kuehne Logistics University I researched reinforcement learning for multi-echelon supply chain decisions. Today I do cross-team ML engineering for ads recommendation and bidding at Huawei's Ireland Research Center.

Alongside client work, my own projects push into causal auditing, federated learning, human-in-the-loop assistants and LLM serving performance. Whether you need a technical partner for an AI product, an ML lead for a critical system, or an outside opinion on an architecture you're about to commit to, the work looks the same: understand the constraint, measure the baseline, ship something maintainable.