Staff Machine Learning Engineer, Recommendation Systems

Nu is the leading digital bank in Latin America serving 135 million customers across Brazil Mexico and Colombia. The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services.

Guided by its mission to fight complexity and empower people Nu caters to customers complete financial journey promoting financial access and advancement with responsible lending and transparency. The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns.

Nus impact has been recognized in multiple awards including Time 100 Most Influential Companies Fast Companys Most Innovative Companies and Forbes Worlds Best Banks.

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Were 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.

Youll 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.

Youll 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 thats tooling process or technical debt.

Were 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 thats 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. Youll 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

Our recruitment process may involve the use of artificial intelligenceenabled tools such as automated interview transcription and analysis to support the evaluation process. Artificial intelligence is not used to make final hiring decisions; all decisions are made by human reviewers.

Required Experience:

Staff IC