The Role As a Staff Machine Learning Engineer in Fraud and Abuse ML Engineering, you will play a central role in designing, building, and evolving the machine learning systems that safeguard Block's ecosystem from fraud, abuse, and other malicious activity. You will architect and lead the development of high-scale, real-time ML systems that power our fraud decisioning across the Block network, protecting millions of customers and merchants while maintaining seamless user experiences. You Will 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. You Have 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. Technologies We Use and Teach Python, Java and Kotlin Tensorflow and PyTorch AWS, Databricks and Kubernetes MySQL, DynamoDB, Kafka, Spark We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, based solely on the core competencies required of the role at hand, and without regard to any legally protected class. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build an inclusive workplace? Check out our Inclusion & Diversity page Full-time employee benefits include the following: Healthcare coverage (Medical, Vision and Dental insurance) Health Savings Account and Flexible Spending Account Retirement Plans including company match Employee Stock Purchase Program Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance Paid parental and caregiving leave Paid time off (including 12 paid holidays) Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees) Learning and Development resources Paid Life insurance, AD&D, and disability benefits These benefits are further detailed in Block's policies. This role is also eligible to participate in Block's equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans. Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.