Senior ML/AI Modeler, Risk Automation Machine Learning

About Us

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.

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.

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 (Copilots). We also automate workflows end to end completely eliminating the need for manual reviews (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 and priorities to completion by collaborating with relevant 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 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 and 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.

Requirements

• 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+ years 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.
• A curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions that demonstrate value.

Compensation

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. 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

Benefits

Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering.