PayJoy, a Public Benefit Corporation, is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. Our patented technology for secured credit provides an on-ramp for new customers to enter the credit system. Through PayJoy’s point-of-sale financing and card offerings, customers gain access to a modern quality of life. PayJoy’s credit also allows our customers to seize opportunities as micro-entrepreneurs, and acts as insurance for tough times. Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 million customers as of 2025 while achieving solid profitability for sustainable growth.
As a Machine Learning Engineer, you will be responsible for developing, optimizing and deploying the ML models and infrastructure that power our fraud detection capabilities across all of PayJoy’s products and markets.
You will work closely with fraud, engineering, product, risk, and business stakeholders across diverse markets to drive the design, implementation and scaling of ML models, AI agents, and other data products (fraud review queues, transaction authorization system, etc.). Your role will also involve ensuring that we are continuously improving the quality and performance of our models by gathering and integrating new data sources that enhance our predictive capabilities.
You will own the whole lifecycle of our fraud ML models, from the feature generation to the model rollout (design, development, deployment and monitoring). You will also build infrastructure to support both manual and automated decisioning of fraud risk.
You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.
