Coinflow Labs
Machine Learning Engineer - Fraud
$225K–$275K
Chicago · On-site · Full-time · Posted Jun 26, 2026
- Experience
- 5+ years in machine learning, applied data science, or production ML roles.
About the job
Lead the development and deployment of production fraud models and risk decisioning systems using transaction data and partner signals to improve payment approvals and fraud outcomes.
What you'll do
- Build, deploy, monitor, and iterate on fraud models and risk decisioning capabilities.
- Analyze transaction and behavioral data, define fraud metrics, and improve detection and precision.
- Integrate external fraud and risk partners and collaborate with Engineering, Product, and Operations to embed fraud intelligence in payment flows.
What they ask for
- 5+ years in machine learning, applied data science, or production ML roles.
- Experience building payments fraud models with direct acquiring-side exposure (acquirer, PSP, or payment facilitator).
- Track record taking ML projects from proof of concept to deployed production systems.
- Strong foundation in ML, statistics, and feature engineering on high-volume financial data.
Nice to have
- Experience developing, managing, and scaling MLOps pipelines and monitoring systems.
- Experience with real-time or near-real-time fraud scoring systems.
Pay
$225,000 - $275,000 USD (base salary)
AI focus
Build and operate fraud and risk ML models, using transaction and behavioral data and partner signals to improve fraud detection, risk decisioning, and payment approvals.
Model-written summary · the original posting is authoritative