Staff Machine Learning Engineer

About the Role

At AI Core, we are scaling the impact of our AI initiatives to become the primary driver of Nu’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 Nu'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 Nu’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.

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.