Senior Fraud Machine Learning Engineer
Affirm
Build real-time fraud models remotely across Canada with Python, tabular learning, and production machine learning expertise at Affu. As a Senior Machine Learning Engineer on the ML Fraud team, you will develop systems protecting consumers and merchants. You will balance fraud loss, customer experience, and conversion while moving models from prototypes into production. The work spans tabular, graph, and behavioral data, feature pipelines, monitoring, and decision systems. Key Responsibilities:
Lead fraud prediction model development across multiple data types Build feature pipelines and training datasets from signals Run offline experiments and productionize strong approaches Improve model reliability, latency, and operational robustness Monitor health and define retraining workflows as patterns evolve Requirements:
Six-plus years launching machine learning models at scale Strong Python and production-quality coding experience Tabular classification experience with gradient-boosted trees Deep learning framework experience, preferably PyTorch Distributed processing and machine learning lifecycle tooling experience Apply senior machine learning expertise to real-time fraud prevention, production systems, monitoring, and measurable transaction decisions at Affu.
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Lead fraud prediction model development across multiple data types Build feature pipelines and training datasets from signals Run offline experiments and productionize strong approaches Improve model reliability, latency, and operational robustness Monitor health and define retraining workflows as patterns evolve Requirements:
Six-plus years launching machine learning models at scale Strong Python and production-quality coding experience Tabular classification experience with gradient-boosted trees Deep learning framework experience, preferably PyTorch Distributed processing and machine learning lifecycle tooling experience Apply senior machine learning expertise to real-time fraud prevention, production systems, monitoring, and measurable transaction decisions at Affu.
#J-18808-Ljbffr
Reference: WJ-3875_15370641