Machine Learning Director

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.

• 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.