Machine Learning Engineer II

About

Elevate consumer protection with Affirm as a Machine Learning Engineer II in a remote setting. Focus on fraud detection through innovative ML systems, balancing risk and user experience.

As part of the ML Fraud team, you will enhance fraud prediction models and design robust automated systems. This role requires expertise in Python, model evaluation, and experience with deep learning frameworks like PyTorch. Close collaboration with engineering and analytics teams is essential to drive model success and adapt to evolving fraud patterns.

Key Responsibilities

• Develop and iterate fraud prediction models for real-time transactions
• Build and scale feature pipelines with proprietary data signals
• Drive offline experiments and prototype new modeling ideas
• Integrate models into decision systems for operational reliability
• Monitor model health and define retraining processes

Requirements

• 2+ years as a machine learning engineer or PhD in a relevant field
• Strong Python skills and production-quality code writing
• Experience with gradient-boosted decision trees and deep learning frameworks
• Familiarity with distributed data processing frameworks such as Spark
• Proficiency in ML lifecycle tools for monitoring and orchestration

Make a significant impact on transforming credit solutions at Affirm while mastering innovative ML technologies.