September 25, 2025
Not specified
On-site/Hybrid
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.
Since Block's inception, our innovative and technology-forward approach to risk management and customer protection has been fundamental to how we invent and build financial products. The Risk team at Block continues this legacy through a sophisticated, technology and science-led approach to protecting our customers and their funds. Our interdisciplinary structure combines Product Development, Science teams (specializing in modeling, analytics, and data science), Operations and key partners including Legal, Compliance and Policy, all working in concert to identify, assess, and solve complex risk challenges across access, fraud prevention and compliance.
This role is part of our Risk Labs team - this team’s mission is aimed at developing advanced deep learning and reinforcement learning based signals and learned representations for machine learning models. In this role, you’ll explore, develop and implement alternatives to traditional feature based ML with state-of-the-art models for solving risk problems. This team works across a wide-swath of the Risk organization touching a variety of use cases and collaborating with a diverse set of teams.
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 employmen