Staff Machine Learning Engineer

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

About the role

At AI Core, we are scaling the impact of our AI initiatives to become the primary driver of Nubank’s most critical decision systems. We are seeking  Machine Learning Engineers to lead high-impact research projects that bridge the gap between state-of-the-art AI and production-grade financial systems. You will be responsible for solving complex, ambiguous problems using Deep Learning and Foundation Models, ensuring our architectures are scalable, efficient, and driving measurable business results.

As an Machine Learning Engineer (MLE), you’re expected to:

Research Execution & Technical Leadership (Complexity & Autonomy)

Lead and execute complex applied research initiatives independently, focusing on building and optimizing architectures (e.g., Transformers, GNNs) that can be deployed across critical use cases like Credit, RecSys, GenAI, and real-time inference.

Address difficult and ambiguous modeling problems that require coordination across various stakeholders (Data, Infra, Product), delivering innovative solutions with a clear focus on medium-term impact.

Bridge the gap between research and production by designing architectures that respect MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-efficiency.

Strategic Impact & Collaboration (Impact)

Develop and deliver innovative solutions that address project-level challenges, focusing on pushing the latest platform and AI research improvements into downstream production models.

Actively participate in cross-functional collaborations , ensuring that research outputs are seamlessly integrated into Nubank's decision-making engines.

Establish technical standards within the AI Core team for experimentation, model evaluation, and code quality, inspiring peers to raise their performance.

Mentorship & Function Contribution (Function Contribution)

Serve as a technical mentor for senior engineers and researchers, providing guidance on deep learning fundamentals, problem formulation, and research methodology.

Actively contribute to the function's growth by participating in mandatory activities like hiring (interview panels) and leading internal task forces to improve our ML lifecycle.

Contribute to thought leadership by participating in research collaborations or internal papers that align with Nubank’s strategic goals.

What are we looking for?

Professional Experience: 5-7+ years in applied AI/ML, with a proven track record of delivering research-driven systems into production environments

Technical Mastery:

Deep expertise in  Deep Learning architectures (Transformers, Multimodal, or GNNs).

Strong coding skills in Python and proficiency with frameworks like PyTorch, JAX, or TensorFlow .

Solid understanding of MLOps and the constraints of deploying models at scale.