Senior ML/AI Modeler, Risk Automation Machine Learning

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 Risk Automation ML team automates Risk and Compliance investigations and decision making at Block through the application of agentic and generative AI technology. We work globally with partners in Product, Engineering and Operations to ensure that we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform. We are leveraging agentic and generative AI as an integral part of our toolkit to fulfill our mission. Block's machine learning systems monitor billions of payment transactions across traditional payment and blockchain networks and surface suspicious activity (fraudulent, suspicious, illegal activity and brand violations) for trained Operations analyst review and decisioning. We are leveraging generative AI to accelerate historically manually intensive analyst workflows; by adding features in the investigative UX to accelerate agent productivity and enable them to make faster, more informed and accurate decisions (aka Copilots). We also automate workflows end to end completely eliminating the need for manual reviews (aka Autopilots). This is a new and significant opportunity to rethink and optimize Risk Operations at Block at scale. This is an IC role, but the senior level has significant leadership responsibilities that include owning, and driving strategic roadmaps & priorities to completion by collaborating with relevant cross functional stakeholders.

(Work from anywhere: This role can be performed from any location in the United States and Canada) You Will - Experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and/or eliminate manual decision loops altogether. - Own the end to end system including API calls to disparate data sources, advanced prompt tuning, orchestration, metrics and evaluation, productionization and monitoring. - Leverage diverse data sets that include payment transactions, connected users and asset graphs, unstructured text data and user profile information to build transformer based ML models to improve downstream detection tasks. - Work cross functionally with product, platform, engineering and operational stakeholders to deploy production grade systems and monitor and tune ongoing performance. - Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP & AWS) to get the job done. - Leverage agentic tools (Claude Code/Codex/Openclaw) to supercharge your research, development, devOps and documentation work as part of your day to day. You Have - 8+ years of Machine Learning modeling experience. Full stack ML experience is strongly preferred. - A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field. - 3+ yrs experience with AI engineering, Large language models, and a background in traditional NLP techniques is a strong plus for this role. - End to end experience of building and deploying ML/AI to production systems (batch and real time) that are performant at scale. - Experience of independently owning, influencing and driving programs with multiple cross functional stakeholders that have significant business impact.