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AI role · Open offer

Senior ML Engineer — fraud & credit intelligence

Nubank

Full-time
Senior
Data & ML
Hybrid
Rua Capote Valente, 39, São Paulo, SP 05409-000, Brazil · Hybrid
São Paulo, Brazil
BRL 25k–40k/month + equity

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

4 skills2 tools

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: Rua Capote Valente, 39, São Paulo, SP 05409-000, Brazil · Hybrid
Compensation: BRL 25k–40k/month + equity
Experience level: Senior
Team: Data & ML
Benefits & perks: Equity (NYSE: NU), hybrid SP, health plan.
How to apply: Fraud, credit, or personalization ML at fintech scale.
Company site: nubank.com.br
Listed: Jul 3, 2026
Updated: Aug 3, 2026

About this role

What the team is looking for and how this position fits.

Nubank is hiring a Senior Senior ML Engineer — fraud & credit intelligence on the Data & ML team (Hybrid · São Paulo, Brazil). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Nubank is Latin America's largest digital bank — tens of millions of customers — using ML for credit, fraud, and personalization from São Paulo.

Senior ML Engineer (hybrid SP): build real-time scoring, GenAI support tools, and experimentation platforms for Brazilian financial products.

Regulatory context (BACEN) and financial inclusion mission influence model design and explainability requirements.

About Nubank

Public company (NYSE: NU) founded in Brazil; engineering hub in São Paulo.
Data culture with strong MLOps and causal inference practices.
One of the largest ML employers in Latin American fintech.

What you will do

Improve fraud and credit models with calibrated risk and monitoring.
Build feature pipelines for real-time inference at card-transaction scale.
Prototype LLM copilots for support with PII redaction and audit logs.
Partner with risk and legal on model documentation and fairness reviews.

Stack & environment

Python, PyTorch, Spark, SQL, Docker on AWS.
Hybrid São Paulo Capote Valente.

What we look for

Fintech or payments ML at scale; Portuguese professional fluency.
Eligible to work in Brazil.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
SQL
Analytical SQL for features, cohorts, label quality, and experiment analysis at scale.
Spark
Distributed feature generation and batch scoring on large tabular or event datasets.

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

AWSTool
Regular use of AWS in the LLM & generative AI stack—configuration, debugging, and team conventions.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Fraud, credit, or personalization ML at fintech scale.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Spark, and AWS.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · São Paulo, Brazil)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: BRL 25k–40k/month + equity, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on My account, and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Fraud, credit, or personalization ML at fintech scale.

Sign in with a candidate account to apply

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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Senior ML Engineer — fraud & credit intelligence

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Zomato runs food delivery and hyperlocal logistics from Gurgaon with national scale.ML Engineer: ETA, dispatch optimization, and Hindi/English support LLM pilots.MissionsReal-time logistics models during peak meal hours.Evaluated copilots for rider and customer support.Stack &…

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Paymob is Egypt's leading payments fintech — POS, wallets, and merchant services from Smart Village, Cairo.Senior ML Engineer (hybrid Cairo): fraud detection, merchant risk, and Arabic support NLP for MENA expansion.About PaymobYC-backed fintech scaling across Egypt and the Gulf.Smart Village…

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