.About PayJoy PayJoy is a mission-first financial service provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. We lend through our patented technology that turns a smartphone into digital collateral, and our cutting-edge machine learning, data science, and anti-fraud AI allow us to offer the lowest cost and qualify the most customers in the industry. As of 2024 we have brought billions of dollars in credit to 12 million customers, doubling in the last two years while remaining strongly profitable and sustainable for the long term. This role As a Machine Learning Engineer at PayJoy, you will play a critical role in developing and maintaining the core systems and infrastructure that power our data science applications. This position is platform/tooling focused. You will work closely with other engineers, data scientists, risk/fraud analysts, and product managers to build, maintain and improve the whole ML platform where our models and other DS products run. You will also develop tools that help our modeling team to create features, train, retrain, deploy, serve, and monitor ML models. In this role, you will own the process of creating and maintaining scalable tools and infrastructure that handle hundreds of millions of transactions per month, ensuring high performance and reliability with a focus on data as a principle. Your work will be instrumental to enhance the impact of the team as it will be a central point of serving both internal and external services. 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 on our millions of users across the countries we operate in. Responsibilities Collaborate with global teams including Risk, Fraud, Engineering, and Product to deliver world-class data science products to international markets, including ML models, infrastructure, and tools.Own the life cycle (design, development, deployment, delivery, and monitoring) of the infrastructure that powers our ML models that serve 300 million transactions per month and ensure they have optimal performance.Drive the enablement of our modeling team by building new tools or adopting new technologies that will allow them to extract data, generate features, and deploy/serve models with ease.Work with a data-driven mindset and understand the critical importance of handling data properly and safely.Organize frameworks and develop processes in our codebase so that the easy and default coding style is cleanly structured.Mentor other engineers and data scientists about best practices in engineering. Requirements Bachelor's degree in Computer Science, Engineering, or a related field