AI Research Manager - Machine Learning

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 rigorous, multi-quarter work, so the team can pursue ambitious bets instead of being fully absorbed by short-term applied demands. Raise the bar on research rigor and communication: strong experimental design, peer review, and reproducibility. Cultivate the team's standing in the broader research community. Real-world impact is our primary measure of success, but we actively encourage publishing, open-source contribution, and conference presence that