Note: The job is a remote job and is open to candidates in USA. Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. 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, and other adversarial activities across Block.
Responsibilities
- Build and operate real-time and batch ML decisioning systems for payment fraud, scams, identity and account integrity, merchant and marketplace risk, and abuse prevention
- Integrate behavioral, graph, device, network, event-stream, and third-party signals into low-latency model serving, decision APIs, and product controls
- Own the production lifecycle for risk decisions, including data contracts, feature quality, online/offline consistency, monitoring, drift detection, safe rollout, rollback, and incident response
- Develop feedback loops and verified AI-assisted workflows for triage, investigation support, alert clustering, graph exploration, simulation, and post-incident learning
- Partner with modelers, analysts, product, compliance, and operations to balance fraud losses, customer access, false positives, product velocity, support burden, and long-term trust
- Create reusable decision and evaluation capabilities that product services, internal tools, and AI-assisted workflows can safely consume
Skills
- 12+ years building and operating production software and ML systems for business-critical products
- Deep expertise in fraud/risk domains such as payment fraud, identity/account integrity, merchant or marketplace risk, scams, trust & safety, abuse prevention, or compliance decisioning
- Strong production ML judgment across feature pipelines, model serving, evaluation, monitoring, low-latency integration, safe rollout, and incident response
- Sound judgment around false-positive tradeoffs, noisy labels, adversarial behavior, customer harm, and cross-functional decisions
- Experience using AI-assisted engineering tools with appropriate verification, testing, and review for high-stakes systems
- Experience with graph-based fraud detection, behavioral sequence models, embeddings, entity resolution, anomaly detection, or human-in-the-loop review
- Experience building fraud operations tooling for triage, case management, alert clustering, graph exploration, or policy simulation
- Experience with regulated financial services, model governance, auditability, explainability, or decision logging
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning
Company Overview
Company H1B Sponsorship