Machine Learning Engineer - Fraud Risk

A Machine Learning Engineer - Fraud Risk at Rain is responsible for architecting and building scalable ML systems focused on fraud detection, anomaly detection, and behavioral analysis. This role includes developing end-to-end ML pipelines, implementing real-time decision systems, and maintaining ML infrastructure for model monitoring and performance. Collaboration with cross-functional teams is essential to integrate ML models effectively within the transaction ecosystem, while also leading experimentation on model robustness and explainability in a fast-paced environment. The ideal candidate should have at least 5 years of production ML experience, particularly in fraud or risk domains, and expertise in Python and ML frameworks.