Staff Applied Machine Learning Engineer

Job Summary

Focused on reducing payment fraud and abuse, the full-time Staff Applied Machine Learning Engineer will design, build, and operate production ML decision systems while collaborating with cross-functional teams in a remote environment.

Key responsibilities

• Build and operate real-time and batch ML decisioning systems for fraud prevention and risk management
• Integrate various data signals into decision APIs and product controls for low-latency model serving
• Own the production lifecycle for risk decisions, including monitoring, incident response, and safe rollout

Required qualifications

• 12+ years of experience in building and operating production software and ML systems
• Deep expertise in fraud/risk domains such as payment fraud and abuse prevention
• Strong production ML judgment across model serving, evaluation, and incident response
• Experience using AI-assisted engineering tools with appropriate verification and testing
• Sound judgment around false-positive tradeoffs and cross-functional decision-making