Senior Machine Learning Engineer - Fraud

Skills

About the Role

You will develop fraud detection models from experimentation through production deployment. You will investigate fraud patterns, engineer training data and features, design experiments, build reproducible pipelines, and improve model performance using customer outcomes.

Requirements

• 7+ years of professional machine learning, applied science, or ML software engineering experience.
• Experience designing, training, tuning, deploying, and evaluating models in production.
• Machine learning and statistical fundamentals including feature engineering, experiment design, and model evaluation.
• Knowledge of gradient-boosted trees and neural networks.
• Experience addressing label quality, data leakage, class imbalance, and generalization.
• Python and SQL proficiency.
• Experience with PyTorch, scikit-learn, XGBoost, or equivalent frameworks.
• Experience leading end-to-end machine learning projects.

Responsibilities

• Investigate fraud patterns and model errors to identify signals and improve detection.
• Develop training datasets and predictive features.
• Design, train, tune, and evaluate machine learning models.
• Design experiments to evaluate features and models.
• Build data and training pipelines for reproducible experimentation.
• Deploy models while balancing quality, latency, cost, and reliability.
• Lead machine learning projects through model release.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 401(k)