Senior Machine Learning Engineer

The role

Build, train and deploy machine learning models that drive credit, fraud, risk and personalization decisions at scale. Work across the full modeling lifecycle, from framing business problems to monitoring models in production, and increasingly include Generative AI and Agentic Engineering.

What you will do

• Frame ambiguous business problems as well-defined modeling problems
• Design, build and validate machine learning models with statistical rigor
• Engineer and maintain features and datasets for training and inference
• Deploy and maintain models in batch and real-time scenarios, with monitoring
• Lead modeling projects end-to-end, from framing to delivery and iteration
• Contribute to the design and maintenance of the modeling codebase, platforms and tooling
• Translate business needs into modeling strategies aligned with the architecture
• Partner with technical and business stakeholders to deliver high-impact models
• Share knowledge, mentor peers and support ML and data literacy initiatives

Required qualifications

• 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 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 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

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 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

Before you apply

• Recruitment may use AI-enabled tools such as automated interview transcription and analysis; final hiring decisions are made by human reviewers
• Nu does not provide individualized technical feedback to candidates

About the company

Nu serves more than 140 million customers with a mission to fight complexity and empower people. It uses proprietary technology and data at scale to power a digital platform focused on financial access, advancement and transparency.