Staff Applied Machine Learning Engineer - Fraud & Abuse

What this role involves

This Staff Applied Machine Learning Engineer role focuses on designing, building, and operating production ML decision systems for fraud and abuse prevention across Block's products. The position requires deep expertise in fraud/risk domains and end-to-end ownership of production systems. The role involves collaboration with cross-functional teams to balance fraud losses and customer access.

Skills this posting asks for

• machine learning
• fraud detection
• production ml decision systems
• feature pipelines
• model serving
• evaluation
• monitoring
• low-latency integration
• safe rollout
• incident response
• graph-based fraud detection
• behavioral sequence models
• embeddings
• entity resolution
• anomaly detection
• human-in-the-loop review
• ai-assisted engineering tools

Requirements

• 12 years of experience
• Level: staff

From the employer’s posting

Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and…