Machine Learning Engineer Manager (AI Platform) - Nubank

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 and this is still just the beginning of the purple future we're building.

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.

We are looking for a Manager who is passionate about creating solutions that push the boundaries of our current stack. You will help us move beyond basic DS work to abstract the complexities of the entire ML lifecycle—from training and deployment to serving and governance.

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:
As the ML Manager for the AI Platform, you will combine technical leadership with people management. You will lead a squad of 11 Machine Learning Engineers (varying from Senior to Intern levels) and work closely with a Staff ML Engineer and a Product Manager.

• 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

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/