Staff Machine Learning Engineer
Nubank is hiring a Staff Machine Learning Engineer in Palo Alto, United States. It pays $230k-$345k a year and Level rates it ; you can apply on Nubank.
Level's read on this job
- On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 16% above the typical machine learning engineer posting on Level.
- The posting allows some remote work.
- Tools and skills the posting cites include PyTorch, TensorFlow and JAX.
- Level lists 103 other open roles at Nubank.
AI in this role
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 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. For more details, visit https://building.nu.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
How we rate this
Staff Machine Learning Engineer at Nubank rates 94 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- This job starts at
- $230k
- Typical machine learning engineer job
- $198k
This posting starts 16% above the typical machine learning engineer job. See machine learning engineer jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you decide that one model's output is better than another's for a given task?
- Tell me about a research question you investigated. What did you find?
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: ML Ops, AI Evaluation, AI Research, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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