Staff Applied ML Engineer - Financial Crime

Build and ship deep learning and graph-based ML models for real-time financial crime detection at Wise. Own ML architecture strategy, define model and training/serving patterns, and create reusable end-to-end pipelines from experimentation to production deployment. Prototype foundation model and embedding approaches for transaction representation, partner on evaluation and causal measurement, and mentor engineers and data scientists within Risk ML’s Risk Modelling pillar.