Staff Machine Learning Engineer (Modeling), Support

Block (Square)·Seattle, WA, United States of America·onsite
crypto:applicationengineeringIC611003 Risk - Prod Dev - Square
Compensation
Not disclosed
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 store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us. The Role Block's Support ML Modeling team is a central driver of innovation in customer support experiences across our entire ecosystem—including Cash App, Square, and other business units. We are dedicated to advancing the state of intelligent, automated support through machine learning and generative AI. From customer-facing chatbots to smart internal tools for agents, our team builds high-impact, scalable systems that improve support quality, efficiency, and accessibility. We're building the future of support at Block: one powered by AI, voice interfaces, and smart automation. We're looking for candidates with a passion for intelligent systems, practical ML experience, and a desire to build product-driven solutions. Our ideal candidate is a leader in the field, with a proven track record of building ML systems that can accelerate our ability to scale our conversational AI initiatives. You Will Lead the end-to-end delivery of multiple ML initiatives, from planning and design through rollout, documentation, and long-term maintenance Partner strategically with risk, product, engineering, design, and operations leaders to define and drive long term ML roadmaps, informed by domain expertise and industry trends Guide the team’s direction, identifying new ML/AI opportunities and advising leadership on strategic tradeo