Machine Learning Lead

About this role

About Coinflow

Coinflow is the next-generation payment service provider revolutionizing global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant settlement. Coinflow enables businesses to grow faster with instant settlement, fraud & chargeback indemnity, global pay-ins, multi-currency FX, and unified payouts. Founded in 2023, the company serves marketplaces, fintechs, remittance providers, gaming platforms, and ecommerce merchants worldwide.

Since our seed round in 2024, we’ve achieved 23x revenue growth and scaled to multi-billion-dollar annual transaction volume. In response to this growth, Coinflow announced a $25M Series A https://coinflow.cash/blog/coinflows-series-a in October 2025—led by Pantera Capital, CMT Digital, Coinbase Ventures, Jump Crypto, and Reciprocal Ventures—accelerating our mission to power the world’s fastest-moving businesses with innovative, reliable global payments.

Coinflow is proudly headquartered in Chicago, IL. Learn more at coinflow.cash http://coinflow.cash.

Role Overview:

Coinflow is seeking a Machine Learning Lead to own the fraud and risk intelligence layer at the core of our platform.

This is a zero-to-one role. You will be our second dedicated ML hire and will build our fraud detection and risk decisioning capabilities from the ground up. That means digging into large-scale transaction and behavioral data, building and shipping production fraud models, defining what good looks like, and continuously raising the bar on detection and precision as our volume and merchant base scales.

The ideal candidate has hands-on experience building fraud models on the acquiring side of payments—card-present or card-not-present, authorization decisioning, chargeback reduction, or related risk systems—and is motivated by the challenge of building something that does not yet exist.

Key Responsibilities

- Build Coinflow's fraud detection and risk decisioning capabilities from zero, including 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—detection rate, false positive rate, chargeback rate, dispute win rate—and continuously improve 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

- Establish the foundation for ML and data practices across the company

- Help shape Coinflow's long-term fraud, risk, and ML roadmap

Required Qualifications

- 5+ years of experience in machine learning, applied data science, or production ML roles

- Demonstrated experience building fraud models in payments, with direct exposure to the acquiring side—acquirer, PSP, or payment facilitator environment

- Proven track record of taking an Machine Learning project from ideation to finished product, from proof of concept notebooking to fully-deployed, productionalized modeling systems.

- Experience in developing, managing, and scaling MLops pipelines and monitoring systems to manage retraining schedules and RT metrics for performance visibility.

- Experience in scoping cloud computational requirements for scalable ML projects across storage accounts, containers, virtual machines, clusters, and sizes.

- Deep familiarity with acquiring-side fraud dynamics: authorization fraud, card-not-present fraud, friendly fraud, chargeback patterns, and merchant risk

- Experience taking fraud or risk models from zero to production in a real system

- Strong foundation in ML, statistics, and feature engineering on high-volume financial data

- Comfortable owning ambiguous problems end-to-end and creating structure where none exists

- Strong collaborator with the ability to work across Engineering, Product, and Ops

Preferred Qualifications

- Experience at an acquirer, ISO, PayFac, or payments infrastructure company

- Familiarity with card network rules, dispute/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 (a plus, not a requirement)

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

The base salary range for this role is $160,000 to $220,000 USD. The actual base salary offered depends on a variety of factors, including but not limited to experience, education, skills, qualifications and business needs.

In addition, the employee who fills this role will be eligible for an equity grant, allowing you to share in the long-term success of the company. You will also have access to a wide array of benefits, including health and wellness benefits, 401(k) savings plan, and flexible time off.

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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