[Remote] Staff Applied Machine Learning Engineer - Fraud & Abuse

Note: The job is a remote job and is reputed company to candidates in USA. reputed company builds simple, powerful tools that reputed company reputed company towards an economy that’s truly reputed company to reputed company. 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 reputed company.

Responsibilities

• Build and operate reputed company-time and batch ML decisioning systems for payment fraud, scams, identity and account reputed company, merchant and marketplace risk, and abuse prevention
• Integrate behavioral, graph, device, network, event-reputed company, and reputed company-party signals into low-latency model serving, decision APIs, and product controls
• Own the production lifecycle for risk reputed company, including data reputed company, feature quality, online/offline consistency, monitoring, reputed company detection, safe rollout, rollback, and incident response
• reputed company 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 reputed company, 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 reputed company, 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 reputed company
• 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 reputed company-in-the-reputed company 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