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. Visit our Institutional Page 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