About Nu

Nu is the leading digital bank in Latin America, serving 135 million customers across Brazil, Mexico, and Colombia. The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services.

Guided by its mission to fight complexity and empower people, Nu caters to customers’ complete financial journey, promoting financial access and advancement with responsible lending and transparency. The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns.

Nu’s impact has been recognized in multiple awards, including Time 100 Most Influential Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Banks.
Visit our institutional page: https://www.nu.com/2026-en

AI Research Manager

About Nubank

Nubank is one of the world's largest digital financial services platforms, recognized by Time 100, Fast Company, and Forbes for leading an industry transformation. Driven by our mission to fight complexity and empower more than 130 million customers, we leverage data and proprietary technology to build the future of financial services. Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.
We are executing an AI-first transformation. The AI Core Research team owns Nubank's forward-looking research agenda: the foundational capabilities that compound into long-term advantage rather than incremental wins. The quality of this team directly shapes whether we lead or follow over the next 24 months.

About the role

As AI Research Manager, you will own the operating health and execution of Nubank's ML research agenda. This is a dedicated people-management role for a small, high-talent-density team of world-class researchers, partnering closely with senior technical leads who drive the scientific direction.
The team works on a portfolio of research bets on a one-to-four-quarter horizon. This work compounds into the production capabilities Nubank will depend on. Current and upcoming bets include:

• Next-generation nuFormer architectures: proprietary transformers that learn from raw transaction sequences and power key production credit decisions

• Multitask and multi-target modeling: single models serving many high-impact prediction tasks at once

• Training and inference efficiency: distillation, quantization, sparsity, and parallelism to run state-of-the-art models economically at our scale

• Causal modeling and policy optimization: moving beyond prediction to the decisions and policies those predictions should drive

• World models: open-ended models that reason about a customer's full financial life

• Recommendation systems: extending the backbone to app events, engagement, and personalization signals

• Embeddings and representation learning: semantic IDs, contrastive learning, and reusable representations used across the bank

• Real-time and continual learning: low-latency inference and models that adapt over time

Your job is to make exceptional science happen: build the conditions, focus, and operating rhythm that researchers do great work.
Location: Palo Alto, US

You'll be responsible for

People & Team Leadership

• Lead, mentor, and advocate for a team of world-class ML researchers, fostering an environment of psychological safety, high ambition, and rigorous scientific inquiry.

• Own the operating health of the team, including performance, career growth, hiring, and compensation cycles for elite individual contributors who often operate at staff-and-above technical depth.

• Attract and retain top-tier research talent in a competitive market, and build a reputation for the team as a place the best researchers want to be.

Research Operations & Execution

• Own the operating cadence of a portfolio of two-to-three concurrent, quarter-scale research bets, from problem framing and OKRs through progress tracking and clear go/no-go decisions.

• Allocate scarce, high-value resources, most notably GPU capacity, across competing research priorities, balancing exploration against the bets most likely to compound.

• Protect deep-focus research time. Sustaining a long-term agenda in a fast-moving company means deliberately creating the space for