Senior Machine Learning Engineer

Nubank; São Paulo, Campinas, Belo Horizonte, Rio de Janeiro; Hybrid; BRL 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Food/Meal Card

Public Transportation Commuting Benefi

NuCare – Psychological, Financial and

Life Insurance, Medical Plan andDental

NuLanguage – Language Course Program

Nucleo – Learning platform

Extended Parental Leave, Daycare Allow

Work-from-home Allowance

Gym Partnerships

30 days of paid vacation

Relocation Assistance Package

Job summary

Nubank is seeking a Machine Learning Engineer to own end-to-end modeling—framing problems, engineering features, training, deploying, and monitoring models at scale. You’ll build models for credit, fraud, risk, and personalization, shaping AI-native experiences for millions of customers.

You’ll collaborate across teams, ship production-grade models, and explore Generative AI. The role embraces hybrid work, strong engineering rigor, and impact-driven delivery.

Qualifications

• Strong foundation in statistics and ML theory.
• Proficiency in Python and ML libraries (scikit-learn, PyTorch, TensorFlow, XGBoost).
• Experience training, validating, and deploying ML models in production.
• Ability to write efficient SQL and work in analytical environments.
• Excellent communication and collaboration with technical and business stakeholders.

Responsibilities

• Frame business problems as ML problems and design modeling strategies.
• Engineer, train, validate, and deploy ML models at scale.
• Maintain features and datasets for training and inference.
• Monitor models in production with metrics and observability.
• Lead end-to-end modeling projects and iterate based on feedback.
• Contribute to code quality and tooling for modeling pipelines.

Skills

Statistics

ML theory

Python

ML libraries

SQL

Communication

Production-grade models

Tools

scikit-learn

PyTorch

TensorFlow

XGBoost

Job description

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

Machine Learning Engineer at Nubank

At Nubank, Machine Learning Engineers sit at the core of how we make decisions at scale. We build, train, and deploy models that drive credit, fraud, risk, personalization decisions and a growing set of AI-native experiences for millions of customers every day. We do it with engineering rigor, statistical depth, and a deep focus on impact.

Our MLEs work across the full modeling lifecycle: framing business problems as ML problems, engineering features, training and validating models, and deploying and monitoring them in production. We value small, independent teams that move fast, own their decisions end-to-end, and hold themselves to a high bar for quality and craft.

Increasingly, that work also includes Generative AI and Agentic Engineering. Depending on the problem, our engineers design and build systems that combine models, tools, workflows, evaluation loops, and human oversight to solve real business tasks reliably in production.

We strive for state-of-the-art ML practices that currently include a variety of technologies. While we value candidates that are familiar with them, we are also confident that engineers who are interested in joining Nubank will be able to learn from our team.

• Large-scale model training and experimentation pipelines
• Feature engineering and feature stores feeding both batch and real-time models
• Model deployment and serving in production, with monitoring through operational and business metrics
• Distributed data processing for training datasets at scale
• Continuous Integration and Deployment into AWS and Kubernetes
• Experiment tracking, model versioning, and reproducibility tooling
• A robust data platform built on modern ETL/ELT practices

As a Machine Learning Engineer, you’re expected to:

• Frame ambiguous business problems as well-defined modeling problems
• Design, build and validate machine learning models, ensuring statistical rigor and business relevance
• Engineer and maintain features and datasets used for training and inference
• Deploy and maintain ML models in both batch and real-time scenarios, integrating them with other systems and monitoring through operational and business metrics
• Lead modeling projects end-to-end — from problem framing and stakeholder alignment to delivery, monitoring and iteration
• Contribute to the design, documentation, maintenance and optimization of our modeling codebase, platforms and tooling
• Translate business needs into modeling strategies aligned with Nubank's architecture and long-term goals
• Partner with technical and business stakeholders to define strategies and deliver high-impact models
• Share knowledge, mentor peers and contribute to ML and data literacy initiatives across Nubank

What We're Looking For

• Strong foundation in statistics, machine learning theory and modeling techniques (e.g. regression, tree-based models, deep learning)
• Programming experience in Python and familiarity with ML libraries (e.g. scikit-learn, PyTorch, TensorFlow, XGBoost)
• Experience training, validating, and tuning models, with solid understanding of overfitting, bias-variance tradeoff and evaluation metrics
• Understanding of the ML model lifecycle, from training and evaluation to deployment and monitoring
• Ability to write efficient SQL queries and work with analytical data environments
• Strong communication skills to collaborate with both technical and business stakeholders
• Passion for building high-quality, production-grade models

Nice to Have

• Experience with cloud platforms such as AWS, GCP or Azure
• Familiarity with distributed systems, microservices and asynchronous architectures
• Experience with feature stores, MLOps tooling and experiment tracking (e.g. MLflow, Feast, Airflow)
• Knowledge of data architecture patterns (Data Lake, Data Warehouse, Data Mart)
• Experience with data visualization tools (Looker, Power BI, Tableau or similar)
• Knowledge of software engineering best practices: testing, clean code, documentation

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 and Dental Plan
• NuLanguage – Language Course Program
• Nucleo – Our learning platform
• Extended Parental Leave, Daycare Allowance and Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model

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/

Our recruitment process may involve the use of artificial intelligence-enabled 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.
To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works here