Senior ML/AI Modeler, Risk Automation Machine Learning

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 for trained Operations analyst review and decisioning. We build Copilots to accelerate agent workflows and Autopilots to automate workflows end-to-end.

This is an IC role with significant leadership responsibilities, including owning and driving strategic roadmaps and priorities to completion.

You Will

• Experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and eliminate manual decision loops.
• 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 (payment transactions, connected user/asset graphs, unstructured text, user profiles) to build transformer-based ML models for downstream detection tasks.
• Work cross-functionally with product, platform, engineering, and operational stakeholders to deploy production-grade systems and monitor ongoing performance.
• Use Python ML stack, LLMs, PyTorch, Snowflake, Airflow-based tools, data platforms, and cloud services (GCP and AWS).
• Leverage agentic tools to accelerate research, development, DevOps, and documentation.

You Have

• 8+ years of Machine Learning modeling experience (Full stack ML experience strongly preferred).
• A Master's or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field.
• 3+ years of experience with AI engineering, Large Language Models, and a background in traditional NLP techniques (strong plus).
• End-to-end experience building and deploying ML/AI to production systems (batch and real-time) performant at scale.
• Experience independently owning, influencing, and driving programs with cross-functional stakeholders.
• Growth-oriented mindset with the ability to think from first principles.

Application Guidelines

• Candidates may submit up to 9 active applications within a 60-day period.
• Reapplications to the same role are accepted 90 days after a previous application review.