Staff Machine Learning Engineer, Fraud & Abuse

Block is a company focused on increasing access to the global economy through technology. They are seeking a Staff Machine Learning Engineer to design and build machine learning systems that protect their ecosystem from fraud and abuse, ensuring a seamless user experience for millions of customers and merchants.

Responsibilities:

• Build and maintain real-time and batch data pipelines/APIs to support ML model inference at scale
• Design elegant ML pipelines and services, prototype new approaches, and productionize solutions at scale
• Collaborate with product and engineering teams to define data models and schemas for consistent and structured data flow
• Integrate and enrich diverse internal and third-party data sources to enhance our feature store and modeling capabilities
• Ensure data quality and completeness through automated validation, monitoring, and alerting
• Develop new triggers and event hooks that support enhanced risk evaluations and detections
• Participate in SEV management by rapidly integrating new data, deploying new features, and implementing stopgap controls to mitigate risk
• Apply ML and engineering best practices to shape how Block develops, tests, and maintains ML-platform solutions
• Support the integration of risk decisions and scores into downstream systems, ensuring they are consumed and acted upon correctly

Requirements:

• 12+ years of experience in software development and demonstrated technical initiative and leadership on previous machine learning projects
• A proven ability to shape how teams effectively adopt and evolve AI practices; driving adoption of AI-first workflows by coaching leaders, identifying scalable use cases, and embedding quality and accountability in team norms
• Experience leading experimentation cycles and building a shared understanding of how AI drives business outcomes
• Curiosity and a passion for Block's mission of economic empowerment
• Experience helping your teammates grow through mentorship and providing constructive feedback
• A desire to be hands-on and help invent the future of AI
• The ability to work autonomously in the rapidly evolving world of ML
• Build and maintain real-time and batch data pipelines/APIs to support ML model inference at scale
• Design elegant ML pipelines and services, prototype new approaches, and productionize solutions at scale
• Collaborate with product and engineering teams to define data models and schemas for consistent and structured data flow
• Integrate and enrich diverse internal and third-party data sources to enhance our feature store and modeling capabilities
• Ensure data quality and completeness through automated validation, monitoring, and alerting
• Develop new triggers and event hooks that support enhanced risk evaluations and detections
• Participate in SEV management by rapidly integrating new data, deploying new features, and implementing stopgap controls to mitigate risk
• Apply ML and engineering best practices to shape how Block develops, tests, and maintains ML-platform solutions
• Support the integration of risk decisions and scores into downstream systems, ensuring they are consumed and acted upon correctly