Senior Machine Learning Engineer (Fraud)

Responsibilities

• You will lead development of new fraud prediction models using a mix of approaches for tabular, graph, and behavioral data
• You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.
• You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
• You productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.
• You will instrument and monitor model and data health, and help define retraining/backtesting workflows as fraud patterns evolve.
• Identify and implement foundational improvements to how the team builds models.
• You will collaborate across Engineering, Fraud Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.
• What we look for
• You have 6+ years experience researching, training, tuning and launching ML models at scale. Relevant PhD can count for up to 2 years of experience.
• Track record of delivering high impact machine learning models in a low latency live setting

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