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 foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level, working across business groups and around the globe to develop inclusive policies, forecast finances, give legal counsel, safeguard systems, and nurture new initiatives.

About 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 a safe user experience for customers while minimizing or eliminating bad activity on our platform. We leverage agentic and generative AI to accelerate historically manual analyst workflows, improve productivity, and enable faster, more informed decisions (Copilots) or automate workflows end-to-end (Autopilots). This role offers the opportunity to rethink and optimize Risk Operations at scale.

This is an individual contributor role with significant leadership responsibilities, including owning and driving strategic roadmaps and priorities by collaborating with cross-functional stakeholders. This role can be performed from any location in the United States and Canada.

Responsibilities

• Experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and/or 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, user and asset graphs, unstructured text data, and user profile information) to build transformer-based ML models that improve downstream detection tasks.
• Work cross-functionally with product, platform, engineering, and operational stakeholders to deploy production-grade systems and monitor ongoing performance.
• Use the Python ML stack, LLMs, PyTorch, Snowflake, Airflow-based tools, data platform, and cloud services (GCP & AWS) to execute projects.
• Leverage agentic tools (Claude Code/Codex/Openclaw) to supercharge research, development, DevOps, and documentation.

Requirements

• 8+ years of Machine Learning modeling experience. Full-stack ML experience is strongly preferred.
• A Master’s or advanced degree in computer science, data science, operations research, applied math, statistics, physics, or a related technical field.
• 3+ years of experience with AI engineering, Large Language Models (LLMs), and a background in traditional NLP techniques (a strong plus).
• End-to-end experience building and deploying ML/AI systems (batch and real-time) that are performant at scale.
• Experience independently owning, influencing, and driving programs with multiple cross-functional stakeholders for significant business impact.
• A curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions.

Benefits

Every benefit offered is designed to empower you to do the best work of your career while building the life you want. Offerings include:

• Remote work options.
• Medical insurance.
• Flexible time off.
• Retirement savings plans.
• Modern family planning support.

For more details, visit Block’s benefits page.

Pay

Block takes a market-based approach to pay, which may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions.

• Zone A: $228,700—$343,100 USD
• Zone B: $217,300—$325,900 USD
• Zone C: $205,900—$308,900 USD
• Zone D: $194,500—$291,700 USD

To find a location’s zone designation, refer to this resource. If a location of interest is not listed, contact a recruiter for additional information.