Senior Machine Learning Engineer

Join our team as a Senior Machine Learning Engineer, where you will be responsible for full-stack ML model development for the detection and prevention of financial crime. You will own and evolve the Dynamic Risk Score, handle a portfolio of transaction rules, and set up continuous monitoring of model and rule performance. You will also participate in infrastructure development for ML model operationalization. The ideal candidate will have at least 5 years of experience as a Machine Learning Engineer or Full-stack Data Scientist, strong skills in SQL and Python, and a quantitative education.

Développement complet de modèles d'apprentissage automatique pour la détection et la prévention de la criminalité financière.

Responsibilities

• Responsabilité et évolution du Dynamic Risk Score (DRS) sur tous les marchés, y compris le scoring quotidien de l'ensemble de la base client.
• Mise en place d'une surveillance continue des performances des modèles et des règles en production, et développement du cadre champion-challenger.
• Experience with model monitoring and champion-challenger / A-B evaluation in production. Exposure to graph modeling or foundation models/embeddings is a plus

Requirements

• A quantitative education (math, engineering, economics, or CS) and full working proficiency in English
• Critical, analytical thinker — proactive, result-driven, comfortable working with little supervision in a start-up setting
• Strong in SQL and Python, and with cloud data platforms (e.g. Databricks)
• Strong architectural skills — able to design and improve infrastructure that serves models of varying complexity
• At least 5 years as a Machine Learning Engineer or Full-stack Data Scientist, with production deployment experience (incl. API services like FastAPI)