Machine Learning Director

Job description

About PayJoy 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. This role PayJoy is proud to be an Equal Employment Opportunity employer and we welcome and encourage people of all backgrounds. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. PayJoy Principles Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening As PayJoy’s ML Platform Director, you will lead a team of very talented Machine Learning Engineers and Software Engineers that are responsible for the end-to-end ML ecosystem at PayJoy. This includes ML infrastructure: feature stores (online and offline), model serving, ETL/feature architecture and the infrastructure that helps us serve our customers like our internal offers API. You will bridge the gap between business strategy (Risk, Fraud, Product) and technical execution, ensuring that our ML infrastructure is scalable, secure and world-class. You are a leader who enables senior-level engineers to solve the company’s most complex problems, fostering an environment where innovation meets production-grade reliability. 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. Key Responsibilities Define the technical roadmap for our ML platform, modeling and internal APIs infrastructure, moving beyond individual projects to oversee the long-term sustainability of our "assembly line" approach to data products and ML model + offers serving. Mentor and manage a team of Staff and Senior-level ML Engineers. Foster a culture of technical excellence, focusing on system design, scalability and code quality. Act as the primary liaison between Data Science/ML Engineering and business stakeholders like Risk, Fraud, Engineering and Product. Translate complex business goals into actionable technical requirements that the team can execute at scale. Own the long-term vision for our ML infrastructure, including deployment, monitoring and MLOps practices. Ensure that all data products are not only performant but also maintainable and compliant with global safety standards. Guide the professional growth of your direct reports, ensuring they are challenged by the right problems and supported by clear career trajectories. Champion the adoption of new technologies (e.g., LLMs, graph databases) and best practices that keep PayJoy at the forefront of financial ML without sacrificing stability. Requirements PhD or master’s in Computer Science, Statistics, Engineering or a related field 8+ years of hands-on experience in Data Science or ML Engineering, with at least 4+ years in a leadership role managing senior-level or staff-level engineers. A proven track record of designing and delivering large-scale ML systems. You must have a deep understanding of the full ML lifecycle (from feature extraction to production monitoring) and the ability to review system designs and architecture at a high level. Ability to identify bottlenecks in global ML operations and design systematic solutions. You think in terms of platforms, not just individual models. Exceptional ability to communicate complex technical concepts to non-technical stakeholders. You can defend technical decisions to executive leadership and advocate for the "engineering mindset." About PayJoy 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. This role As PayJoy’s ML Platform Director, you will lead a team of very talented Machine Learning Engineers and Software Engineers that are responsible for the end-to-end ML ecosystem at PayJoy. This includes ML infrastructure: feature stores (online and offline), model serving, ETL/feature architecture and the infrastructure that helps us serve our customers like our internal offers API. You will bridge the gap between business strategy (Risk, Fraud, Product) and technical execution, ensuring that our ML infrastructure is scalable, secure and world-class. You are a leader who enables senior-level engineers to solve the company’s most complex problems, fostering an environment where innovation meets production-grade reliability. 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. Key Responsibilities Define the technical roadmap for our ML platform, modeling and internal APIs infrastructure, moving beyond individual projects to oversee the long-term sustainability of our "assembly line" approach to data products and ML model + offers serving. Mentor and manage a team of Staff and Senior-level ML Engineers. Foster a culture of technical excellence, focusing on system design, scalability and code quality. Act as the primary liaison between Data Science/ML Engineering and business stakeholders like Risk, Fraud, Engineering and Product. Translate complex business goals into actionable technical requirements that the team can execute at scale. Own the long-term vision for our ML infrastructure, including deployment, monitoring and MLOps practices. Ensure that all data products are not only performant but also maintainable and compliant with global safety standards. Guide the professional growth of your direct reports, ensuring they are challenged by the right problems and supported by clear career trajectories. Champion the adoption of new technologies (e.g., LLMs, graph databases) and best practices that keep PayJoy at the forefront of financial ML without sacrificing stability. Requirements PhD or master’s in Computer Science, Statistics, Engineering or a related field 8+ years of hands-on experience in Data Science or ML Engineering, with at least 4+ years in a leadership role managing senior-level or staff-level engineers. A proven track record of designing and delivering large-scale ML systems. You must have a deep understanding of the full ML lifecycle (from feature extraction to production monitoring) and the ability to review system designs and architecture at a high level. Ability to identify bottlenecks in global ML operations and design systematic solutions. You think in terms of platforms, not just individual models. Exceptional ability to communicate complex technical concepts to non-technical stakeholders. You can defend technical decisions to executive leadership and advocate for the "engineering mindset."