Nu AI Core Summer PhD Research Internship

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.
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The Nu AI Core Summer Internship Program is a research-focused internship for PhD students working at the frontier of artificial intelligence and machine learning.

Over about 12 weeks, interns collaborate with engineers, applied scientists, and researchers on complex AI challenges. Each intern leads an end-to-end research or applied AI project that combines research methods with large-scale production environments.

The program builds long-term relationships between industry and academia and with emerging AI research talent.

• Duration: ~12 weeks

• Start dates: May–June, aligned with US university calendars

• Location model
  :
  Remote, with one in-person week at Nu's Palo Alto office in Silicon Valley, fully covered by us.

What you get

• Dedicated research mentor

• Ownership of a scoped AI research project

• Access to large-scale datasets and compute infrastructure

• Research talks and technical seminars

• Final research presentation to leadership and AI teams

Interns may work on projects related to:

• Machine learning and deep learning

• Large language models and generative AI

• Recommender systems and ranking models

• AI infrastructure and model optimization

• Responsible AI and model evaluation

Projects typically combine research experimentation with applied system development
, including model design, experimentation, and large-scale evaluation.

This program targets PhD students conducting research in AI and machine learning who are interested in applying their work to real-world systems.

Applicants are typically pursuing a PhD in fields such as:

• Computer Science

• Machine Learning

• Artificial Intelligence

• Statistics

• Mathematics

• Computational Linguistics

• Electrical Engineering

• or related quantitative disciplines.

• Currently enrolled in a PhD program

• Research focus in machine learning, AI, statistics or related areas

• Strong programming skills in Python or similar languages

• Experience working with machine learning frameworks (e.g., PyTorch, Tensor Flow)

• Experience designing experiments and evaluating models

• Experience working with large datasets or training ML models

Strong candidates may also demonstrate:

• Publications at top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, KDD, Rec Sys, CVPR, CIKM or equivalent-conferences for related fields)

• Experience working with large-scale ML systems or distributed training

• Experience with LLMs, generative AI, or foundation models

• Open-source contributions in AI or ML

• Experience collaborating in interdisciplinary research environments

We are particularly interested in candidates who demonstrate:

• Strong research rigor and experimental methodology

• Ability to translate research ideas into practical systems

• Track record of identifying novel research directions or reframing existing problems

• Intellectual curiosity and independent problem solving

• Collaboration with engineers and cross-functional teams

• Interest in deploying AI systems with real-world impact

• Top Tier Medical Insurance

• Top Tier Dental and Vision Insurance

• Life Insurance and AD&D

• Extended maternity and paternity leaves

• Nucleo
  - Our learning platform of courses

• Nu Language
  - Our language learning program

• Nu Care
  - Our mental health and wellness assistance program

• 401K

• Saving Plans
  - Health Saving Account and Flexible Spending Account

Remote, but only for USA PhD students

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