Staff Machine Learning Engineer, Recommendation Systems

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We're looking for a Staff Machine Learning Engineer to help lead the technical direction of our recommendation systems. This is a hands-on senior individual contributor role for someone who has shipped ML systems at scale before and wants to shape how Nubank builds them going forward.

You'll be a technical anchor for the team, working on problems like retrieval, ranking and multi-objective optimization pipelines, and the infrastructure that lets these systems serve millions of customers with low latency and high reliability.

You'll be responsible for

• Setting technical direction for recommendation systems, including architecture decisions that other engineers will build on for years.
• Designing and building production ML systems for retrieval, ranking, and multi-objective optimization that operate at scale and under real latency constraints. You will be hands-on, regularly making coding contributions.
• Leading the most technically demanding projects on the team, from first design through production rollout.
• Partnering with applied scientists to move models from research into reliable, monitored production systems.
• Raising the technical bar for the team: reviewing designs, mentoring engineers, and pushing for better practices around testing, experimentation, monitoring, and system design.
• Working directly with stakeholder teams to understand their recommendation needs and translate them into shared, reusable infrastructure rather than one-off solutions.
• Identifying and fixing the structural issues that slow the team down, whether that's tooling, process, or technical debt.

We're looking for someone who has

• A strong track record building and operating large-scale ML systems in production, ideally recommendation, ranking, or personalization systems.
• Experience building modern recommendation systems, e.g., learned embeddings, semantic IDs, sequence models over long user histories, and conversational recommendation systems.
• Deep experience with the full ML engineering lifecycle: training, deployment, monitoring, data consistency, experimentation, and governance.
• Strong software engineering fundamentals and fluency in Python and/or Scala, or equivalent languages.
• Real experience with the operational side of ML: on-call, incident response, debugging systems under load.
• A track record of technical leadership, whether that's an official title or just being the person a team leans on for the hard calls.
• Comfort working with ambiguity and translating loose business goals into concrete technical priorities.
• Good communication skills. You'll need to explain technical tradeoffs to both engineers and non-technical stakeholders.
• Experience with distributed systems, Spark, or similar large-scale data processing tools is a plus.

Our Benefits

• Opportunity of earning equity at Nu
• Total compensation includes base salary, RSUs and benefits. Base salary range: $230k - $345k
• Medical Insurance
• Dental and Vision Insurance
• Life Insurance and AD&D
• Extended maternity and paternity leaves
• Nucleo - Our learning platform of courses
• NuLanguage - Our language learning program
• NuCare - Our mental health and wellness assistance program
• Extended maternity and paternity leaves
• 401K
• Saving Plans - Health Saving Account and Flexible Spending Account
• Work-from-home Allowance
• Relocation Assistance Package, if applicable.

Role Location

Palo Alto, California
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/