Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

The Role

The Block Financial Crimes Machine Learning team is responsible for detecting, preventing, and reporting illegal activity across all markets in which Square and Cash App operate. We work globally with partners in business, engineering, counsel, and product to ensure we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.

We leverage Machine Learning as an integral part of our toolkit to fulfill our mission. We employ scalable solutions in order to monitor billions of dollars in transactions. We uncover and put an end to money laundering, terrorist financing, and other illegal activities before they impact our users. Additionally, we improve workflow and case tools, adding features that empower investigator productivity and automate the high volume of monitoring. We are looking for Senior Machine Learning Modelers who are interested in solving critical business problems using any and all tools necessary.

You Will

• Build both batch and real-time machine learning solutions for the assessment of financial crimes risk at scale across all global markets in which Square and Cash App operate
• Work closely with stakeholders, business partners, and product engineering teams to ensure that data can be leveraged effectively to build efficient solutions within our regulatory program
• Produce thorough documentation of our program that can withstand regulatory scrutiny
• Proactively identify new opportunities and future needs of our ML teams
• Lead by example by applying ML and engineering best practices
• Stay current on ML developments in the field, foster an environment of continuous learning, and apply new learnings when applicable
• Have a significant impact on influencing team culture and direction

You Have

• 5+ years of software engineering or machine learning experience
• A degree (preferable graduate level) in Computer Science, Engineering, Statistics, Physics, Applied Math or a related technical field
• An ability to maintain critical production software and build new production software from scratch
• Prior experience working with product, engineering, and business to prioritize, scope, design, and deploy ML tooling and infrastructure at scale
• Natural curiosity and desire to grow and help shape all aspects of our growing team
• Excellent written and oral communication skills to both technical and non-technical audiences, and are comfortable working with a cross-functional, globally distributed team

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 an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.

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 a workplace that is fair and square? Check out our I+D page.

Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances