Block
StaffAppliedMachineLearningEngineer-Fraud&Abuse
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Applied Machine Learning Engineer - Fraud & Abuse at Block. Skills: Applied Machine Learning, Fraud & Abuse, ML decision systems, Production ML. Build ML decisioning systems. Integrate signals into models”
What You'll Achieve.
Reduce payment fraud; Reduce account takeover; Reduce identity abuse; Reduce merchant risk; Reduce marketplace risk; Reduce scams; Reduce adversarial activity; Preserve good customer access; Reduce fraudulent activity; Reduce abusive activity; Reduce unsafe activity
Industry & Context.
Incident response; Troubleshooting
What They're Looking For.
Must Have
12+ years production software ML systems, Deep expertise fraud/risk domains, Production ML judgment, Sound judgment false-positive tradeoffs, Experience AI-assisted engineering tools
Nice to Have
Graph-based fraud detection experience, Behavioral sequence models experience, Embeddings experience, Entity resolution experience, Anomaly detection experience, Human-in-the-loop review experience, Fraud operations tooling experience, Regulated financial services experience, Model governance experience, Auditability experience, Explainability experience, Decision logging experience
What You'll Do.
Build ML decisioning systems
Integrate signals into models
Own production lifecycle
Develop feedback loops
Partner with modelers
Create decision capabilities
How You'll Work.
Team & Collaboration
ML modelers; Product engineers; Risk analysts; Compliance partners; Operations teams
Full Job Description
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 As a Staff Applied Machine Learning Engineer focused on Fraud & Abuse, you will design, build, and operate production ML decision systems that reduce payment fraud, account takeover, identity abuse, merchant and marketplace risk, scams, and other adversarial activity across Block. The team optimizes for reliable decisions, safe deployment, and measurable customer outcomes — preserving access for good customers while reducing fraudulent, abusive, or unsafe activity. You should be comfortable owning production systems end to end: data contracts, low-latency inference, batch scoring, feature quality, online/offline consistency, model deployment, monitoring, incident response, rollback, and outcome feedback loops. The work combines large-scale ML decisioning with AI-assisted operations: surfacing evidence, simulating controls, accelerating triage, and improving feedback loops while preserving human judgment in high-stakes decisions. You will work closely with ML modelers, product engineers, risk analysts, compliance partners, and operations teams to respond quickly to evolving abuse patterns without creating unnecessary friction or harm for legitimate customers. You Will Build and operate real-time and batch ML decisioning systems for payment fraud, scams, identity and account integrity, merchant and marketplace risk,
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