Nu AI Core Summer PhD Research Internship

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.

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About the Program

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.

Program Structure

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

Research Areas

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.

Candidate Profile

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.

Basic Qualifications (Application/ Screening Filters)

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, TensorFlow)

Experience designing experiments and evaluating models

Experience working with large datasets or training ML models

Preferred Qualifications

Strong candidates may also demonstrate:

Publications at top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, KDD, RecSys, 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

What We Value

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

Benefits

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

NuLanguage - Our language learning program

NuCare - Our mental health and wellness assistance program

401K

Saving Plans - Health Saving Account and Flexible Spending Account

Location for this opportunity

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