Nubank
Staff Machine Learning Engineer, Recommendation Systems
Part remote, part office, you need to live within commuting distance of a named location.
Hybrid · Palo Alto
Employer listed it 7 weeks ago · Added yesterday
Been open since 7 weeks ago. Long-running listings are sometimes left up after the role is filled.
Salary
$230k to $345k per year
Location
Hybrid · Palo Alto
Timezone
Not stated
Contract
Full-time
Experience
Lead
Category
Data
Stated by the employer in the job description
Remote flexibility
Hybrid
This role is only partly remote, the employer expects time in the office around Palo Alto, Hybrid, so you need to live within commuting distance.
What the employer says
- Source listing states candidate location: "Palo Alto, Hybrid"
- Listing mentions "Hybrid"
What Nomaders makes of it
- Not suitable if you plan to move between countries
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
About Nu
Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.
Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. Visit our Institutional Page
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
Requirements
The employer hasn't listed requirements separately, they're described in the role summary above and on the original listing.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, hybrid, matches where you plan to live and work.
- 2Tailor your CV to the role at Nubank, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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