Staff Machine Learning Engineer
At a glance
Senior Machine Learning Engineering role at Nubank. Palo Alto · full-time · $230,000–$345,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Lead applied research on deep-learning architectures, then adapt them for credit, recommendations, generative AI, and real-time inference
- Solve unclear modeling problems with data, infrastructure, and product partners, aiming for solutions with medium-term impact
- Design production-ready models around MLOps limits, balancing latency, interpretability, and operating cost
- Set team practices for experimentation, model assessment, and code quality, while mentoring experienced engineers and researchers
- Join hiring panels and internal task forces, and contribute to research collaborations or papers tied to strategic goals
What you bring
- At least five years in applied AI or machine learning, including taking research-led systems into production
- Deep knowledge of Transformers, multimodal models, or graph neural networks, plus Python and a framework such as PyTorch, JAX, or TensorFlow
- Understanding of MLOps and the practical demands of deploying models at scale
- Experience with large-scale experiments and A/B tests, and skill in framing ML problems when data is messy or missing
Who this fits
This senior role suits an experienced machine learning engineer who can lead ambiguous research independently, guide peers, and explain technical choices to cross-functional partners. The position is hybrid in Palo Alto, with office attendance at least twice a week.
From the employer
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.
Problem Solving: Sophisticated skills in ML problem formulation and the ability to navigate uncertainty when data is messy or unavailable.
Communication: Ability to communicate complex technical concepts to both technical peers and cross-functional stakeholders, ensuring alignment and buy-in.
Analytical Capacity: Experience with large-scale experimentation and A/B testing to validate research hypotheses.
Our Benefits
Opportunity of earning equity at Nu
Total compensation includes base salary, RSUs and benefits. Base salary range: $230k - $345k
Medical Insurance
Dental and Vision Insurance
Life Insurance and AD&D
Extended maternity and paternity leaves
Nucleo - Our learning platform of courses
NuLanguage - Our language learning program
NuCare - Our mental health and wellness assistance program
Extended maternity and paternity leaves
401K
Saving Plans - Health Saving Account and Flexible Spending Account
Work-from-home Allowance
Relocation Assistance Package, if applicable.
Role Location
Palo Alto, California
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