Senior Machine Learning Engineer - Fraud
Core
Build machine learning systems for fraud detection and prevention using Plaid's network data to identify and stop fraud before it happens.
Role type
Senior Machine Learning Engineer (Fraud Detection)
Builds
Production ML models and data pipelines for fraud detection products
Domain
Financial Technology (FinTech) / Fraud Prevention
Deliverable
production ML models
Required skills
Machine learning lifecycle expertise, predictive pattern identification, training dataset construction, feature engineering, experiment design, model evaluation, Python, SQL, PyTorch, scikit-learn, XGBoost, gradient-boosted trees, neural networks
Preferred skills
Fraud or risk modeling experience, graph-based systems, learned representations, transformers, foundation models
Technologies
PyTorch, scikit-learn, XGBoost
Responsibilities
Investigate fraud patterns and model errors to identify new signals; Develop training datasets and predictive features; Design, train, and tune models; Design experiments to test features and models; Build data and training pipelines; Deploy models with Engineering and ML Infrastructure partners; Independently lead ML projects from experimentation through production
Seniority
Senior, hands-on IC
