Machine Learning Engineer
Coinflow
About Coinflow
Coinflow is a next-generation payments company headquartered in Chicago, pioneering the way money moves globally. We enable merchants and marketplaces to accept payment methods across 170+ countries with instant settlement, AI-driven fraud prevention, and blockchain-based proof-of-delivery.
Backed by leading investors—including Pantera Capital, CMT Digital, Coinbase Ventures, Jump Capital, and Reciprocal Ventures—Coinflow recently raised a $25M Series A to accelerate our mission to modernize cross-border payments.
Since our seed round in 2024, we’ve achieved 23x revenue growth and scaled to a multi-billion-dollar annual transaction volume run rate!
Role Overview:
Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers our platform.
This is a zero-to-one role. You will be the first dedicated ML hire and will own how data and machine learning are developed and applied across Coinflow. You’ll explore large-scale transaction and behavioral data, build models and analytical systems, define what success looks like, and embed intelligence directly into our products and internal tooling.
The ideal candidate is deeply curious, excited to experiment, and motivated by building something that does not yet exist.
Key Responsibilities:
Build and evolve machine learning models and analytical systems that support platform decisioning and product intelligence
Establish the foundation for data and machine learning practices across the company
Define, own, and evolve core metrics across platform health, performance, and risk
Explore transaction and behavioral data to uncover patterns, signals, and new insights
Partner closely with Engineering, Product, and Operations to turn open-ended problems into real systems
Design how models and data systems are evaluated, improved, and trusted over time
Build internal workflows and tooling that support operational and product teams
Help shape Coinflow’s long-term data and machine learning roadmap
Required Qualifications:
4+ years of experience in machine learning, applied data science, or production ML roles
Strong foundation in machine learning, statistics, and analytical problem solving
Experience building models or data-driven systems that operate in real products
Comfort working with ambiguous problems and creating structure where none exists
Strong communication skills and experience collaborating cross-functionally
High ownership mindset with genuine curiosity about messy, real-world data
Preferred Qualifications:
Experience building decisioning, optimization, fraud, risk, or other payments systems
Experience in fintech, payments, or other financial services environments
Experience as an early data/ML hire at a startup
Experience working with high-volume behavioral or financial data
What We Offer:
Competitive compensation including base salary, performance bonus, and meaningful ownership
Opportunity to build the fraud and risk intelligence layer of a rapidly scaling fintech company
Collaborative and innovative work environment with world-class investors
Direct impact on core risk infrastructure and company trajectory during a hypergrowth phase
Join the team rewriting how money moves worldwide—and become a driving force in the $194 trillion cross-border payments market.
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