About this role

📋 Description Lead fraud prediction models using tabular, graph, and behavioral data Build and scale feature pipelines and training datasets Prototype modeling ideas; offline experiments; risk-managed production Productionize models: batch/real-time decisions; improve latency Instrument and monitor model/data health; define retraining/backtesting workflows Collaborate across Engineering, Fraud Analytics, Product, ML Platform 🎯 Requirements 6+ years ML model experience; PhD counts up to 2 Low-latency ML in production Strong Python; production-quality code Tabular classification models (LightGBM/XGBoost/CatBoost) PyTorch experience Distributed data processing + ML lifecycle tooling (Spark; Kubeflow/Airflow/MLflow) 🎁 Benefits Remote-first culture; mostly remote within country Health/dental/vision coverage for you and dependents Flexible Spending Wallets for tech, meals, lifestyle ESPP and equity rewards

Source listing: empllo_remote