Machine Learning Engineer - Fraud

As a Machine Learning Engineer at Coinflow, you own the fraud and risk intelligence layer at the core of our payments platform. This is a founding ML role where you'll lead our first dedicated ML team, building capabilities that combine first-party transaction data with partner signals to optimize approval rates across payment methods and geographies, sharpen risk decisioning during merchant underwriting, and improve fraud detection across global payment methods. You'll work with large-scale transaction and behavioral data, ship production fraud models, and continuously raise the bar on detection and precision as volume and merchant base scale.

What you'll do

• Strengthen Coinflow's fraud detection and risk decisioning capabilities through feature engineering, model development, and production deployment
• Own the full model lifecycle: experimentation, evaluation, monitoring, and iteration
• Define and track core fraud and risk metrics including detection rate, false positive rate, chargeback rate, and dispute win rate, continuously improving them
• Explore transaction and behavioral data to surface new fraud signals and emerging attack patterns
• Partner with Engineering, Product, and Operations to embed fraud intelligence directly into payment flows and internal tooling
• Integrate and orchestrate external fraud and risk partners to get maximum value from their tooling
• Establish the foundation for ML and data practices across the company
• Help shape Coinflow's long-term fraud, risk, and ML roadmap

What you bring

• 5+ years in machine learning, applied data science, or production ML roles
• Demonstrated experience building fraud models in payments, with direct exposure to the acquiring side as an acquirer, PSP, or payment facilitator
• A proven track record taking ML projects from proof-of-concept to fully deployed, productionized systems
• Deep familiarity with acquiring-side fraud dynamics: authorization fraud, card-not-present fraud, friendly fraud, chargeback patterns, and merchant risk
• A strong foundation in ML, statistics, and feature engineering on high-volume financial data
• Comfort owning ambiguous problems end-to-end and creating structure where none exists
• Strong collaboration skills across Engineering, Product, and Operations

Nice to have

• Experience at an acquirer, ISO, PayFac, or payments infrastructure company
• Experience developing, managing, and scaling MLOps pipelines and monitoring systems, including retraining schedules and real-time performance metrics
• Experience scoping cloud compute requirements for scalable ML workloads
• Familiarity with card network rules, dispute and chargeback workflows, and fraud liability frameworks
• Experience as an early or sole ML hire at a startup
• Exposure to real-time or near-real-time fraud scoring systems
• Experience with stablecoin, crypto, or alternative payment rails

What we offer

• Base salary of $225,000-$275,000 USD
• Performance bonus and meaningful equity ownership
• Health and wellness benefits
• 401(k) savings plan
• Flexible time off

About Coinflow

Coinflow is a next-generation payment service provider revolutionizing global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant settlement. Founded in 2023, the company has achieved 23x revenue growth since its seed round and reached multi-billion-dollar annual transaction volume. In October 2025, Coinflow closed a $25M Series A led by Pantera Capital, CMT Digital, Coinbase Ventures, Jump Crypto, and Reciprocal Ventures. Headquartered in Chicago, IL, Coinflow serves marketplaces, fintechs, remittance providers, gaming platforms, and ecommerce merchants worldwide.