Machine Learning Engineer Manager (AI Platform)

About Us

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America. About the Role: AI Platform Team - The mission of the AI Platform team is bold: to democratize AI by empowering every Nubanker—not just Data Scientists—with safe, scalable, and accurate Machine Learning capabilities. Why is this role open: We are scaling. Currently, our structure has grown significantly, and to ensure the organization's health and the growth of our engineers, we are opening this position to lead a dedicated squad. You will take ownership of a team that manages the base infrastructure for the entire Data Science function at Nubank. You'll be responsible for: People Management: Foster a culture of feedback and growth. You will guide the development of your direct reports, conducting performance reviews and helping them navigate their careers. Strategic Roadmap: Translate high-level business goals into actionable technical roadmaps. You will discuss needs with stakeholders and define the "how" and "when." Architecture & Innovation: Explore architecture gaps and opportunities. You won't just maintain; you will challenge the team to explore complex features like scalable parallel processing and better UX for Data Scientists. Execution: Conduct initiatives with autonomy and diligence, ensuring we deliver value while maintaining high engineering standards. Nubank already has well-established tools for basic Data Science work. Your challenge is to take us to the next level. You will push the frontiers of technology to handle massive scale, integrate with multiple complex systems, and democratize access to AI tools across the company. What we are looking for: You don't need to be a hands-on coder 100% of the time, but you must have the technical depth to challenge the team and understand the ecosystem. Experience in Leadership: You have experience managing high-performing engineering teams, sharing feedback, and hiring/developing talent. Domain Expertise: Solid background in ML Engineering, AI, or Data Science, specifically with a focus on MLOps, Infrastructure, and Platform building. Tech Stack Familiarity: You are comfortable discussing and architecting systems involving Kubeflow, SageMaker, and Databricks. The "Builder" Mindset: You enjoy building software. You want autonomy to make decisions and explore edge technologies, similar to the engineering culture found in Big Tech