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Ai Research Manager - Machine Learning

Nubank

USA, Palo Alto
IA

Score da Vaga

80 pontos
Modelo presencial (+70) IA (+10)

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 build a reputation reflecting the quality of the work and help attract the best researchers.

Strategy & Cross-Team Collaboration

  • Partner closely with senior technical leads who drive architecture and scientific direction, aligning operational execution with the long-term research roadmap so that scientific and operating decisions reinforce each other.
  • Ensure clean handoffs from research into production, so breakthrough results land reproducibly in the hands of applied teams rather than stalling as one-off experiments.
  • Translate complex, frontier technical progress (training efficiency, causal inference, novel architectures) into clear, high-impact narratives for executive leadership, connecting research milestones to business outcomes.
  • Bridge foundational research and long-term business strategy, ensuring the team's technical inputs directly enable Nubank's AI-first direction.

We are looking for a person who has

You are an experienced research or engineering manager working at the intersection of cutting-edge AI research and Applied ML. You lead brilliant, highly autonomous researchers without micromanaging, and you know what it takes to sustain an ambitious, long-horizon research agenda inside a fast-moving company. You measure your success by what your team ships and discovers, not by your own keystrokes.

Basic Qualifications:

  • Experience: 3+ years of direct people-management experience leading applied AI research or core machine learning teams at big tech companies, frontier labs, or comparable high-scale environments.
  • Education: M.S. or Ph.D. in Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field, with a strong working understanding of core AI methodologies.
  • Track record: Proven ability to build, scale, and retain high-performing research or advanced applied-science teams.

Preferred Qualifications:

  • Technical depth: This is a management-first role, but deep conceptual familiarity with at least one of our core research areas is highly valued:
    Foundation models & LLMs: pre-training from scratch, scaling laws, training-optimization frameworks, and large GPU-cluster workflows.
    Behavioral & sequential models: sequence models, recommendation systems, and large-scale representation learning for very large user bases.
    Decisioning & optimization: causal inference, policy optimization, constrained optimization, or reinforcement learning.
    Training & inference efficiency: model sparsification, quantization, distillation, or parallelism and partitioning design.
  • Communication: Exceptional storytelling skills, with a track record of translating complex technical milestones into business impact for senior and C-level audiences.
  • Environment: Experience operating in global, distributed teams and navigating the path from foundational research to scalable, production-grade systems.

Why This Role

This is a rare chance to lead frontier AI research with a clear, compounding mission: building the intelligence layer of one of the world's largest digital banks. You'll work alongside strong ML researchers, with the data, compute, and executive backing to pursue genuinely ambitious bets, and to see those bets reach more than 130 million customers.

Location

Palo Alto, United States

 

Our Benefits

  • Total compensation includes base salary, RSUs and benefits. Base salary: $324k
  • Opportunity of earning equity at Nu
  • Medical Insurance
  • 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
  • Work-from-home Allowance
  • Relocation Assistance Package, if applicable.

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/ 

Sobre a área de Inteligência Artificial

A área de Inteligência Artificial é atualmente a que mais cresce no mercado de tecnologia. A revolução dos modelos generativos (GPT, Claude, Gemini) criou uma demanda massiva por profissionais especializados em IA.

As principais áreas de atuação incluem Machine Learning Engineering, MLOps, Prompt Engineering, AI Research e Applied AI. Python, TensorFlow, PyTorch e conhecimento de LLMs são skills essenciais.

Salários na área de IA são os mais altos do setor de tecnologia, com muitas oportunidades de trabalho remoto para empresas internacionais.

Guias de Carreira

Guia de Carreira em Tecnologia

Planejamento, habilidades, entrevistas e crescimento profissional em TI, Ciência de Dados, DevOps e Produto.

Ler guia completo →

Guia de Carreira em Design

UX/UI, Design Gráfico, Design de Produto. Portfólio, ferramentas, entrevistas e crescimento na área de Design.

Ler guia completo →

Guia de Carreira em Marketing

SEO, Mídia Paga, Growth, Marketing de Conteúdo. Certificações, ferramentas e estratégias para crescer no Marketing Digital.

Ler guia completo →

Guia de Carreira em Finanças

Mercado financeiro, investimentos, finanças corporativas, certificações e estratégias para crescer na área financeira.

Ler guia completo →

Guia de Carreira em Comunicacao

Jornalismo, RP, Comunicacao Corporativa, Marketing de Conteudo e Producao Multimidia.

Ler guia completo →

Guia de Carreira em Administracao

Gestao de Empresas, RH, Logistica, Consultoria, Gestao de Projetos e Empreendedorismo.

Ler guia completo →

Guia de Carreira em Dados

Ciencia de Dados, Engenharia de Dados, BI, Machine Learning e IA. Da formacao ao mercado.

Ler guia completo →

Guia de Carreira em Produto

Product Management, Product Ownership, Agile, Scrum e OKRs. Da estrategia a execucao.

Ler guia completo →

Dica do Especialista

Como a Inteligência Artificial Transformou a Procura de Empregos

A Revolução Silenciosa no Recrutamento

Nos últimos anos, a Inteligência Artificial (IA) deixou de ser apenas um conceito futurista para se tornar a principal ferramenta nos departamentos de Recursos Humanos de empresas no mundo todo. Para os candidatos, isso significa que a jornada em busca da vaga ideal mudou drasticamente. Já não basta ter um bom currículo; é preciso entender como os algoritmos leem e avaliam a sua trajetória profissional antes mesmo de um ser humano olhar para ela.

Como as Empresas Estão Usando a IA

O volume de candidaturas online cresceu exponencialmente, o que forçou as empresas a adotarem sistemas automatizados para lidar com a triagem. Os principais impactos incluem:

  • Sistemas ATS (Applicant Tracking Systems): Robôs que analisam milhares de currículos em segundos, buscando palavras-chave, habilidades específicas e cruzando dados com a descrição da vaga. Se o seu currículo não tiver os termos exatos, ele é descartado imediatamente.
  • Entrevistas Automatizadas: Algumas plataformas já utilizam IA para analisar o tom de voz, as microexpressões faciais e a escolha de palavras dos candidatos durante entrevistas gravadas em vídeo.
  • Matching de Candidatos: Algoritmos preditivos vasculham plataformas como o LinkedIn para encontrar candidatos passivos que tenham o perfil exato da vaga, muitas vezes abordando-os automaticamente.

O Lado do Candidato: Como Usar a IA a Seu Favor

Se as empresas usam robôs para filtrar, os candidatos também podem (e devem) usar a inteligência artificial para se destacar na multidão. A IA democratizou o acesso a ferramentas de otimização de carreira.

  1. Otimização de Currículos: Ferramentas baseadas em Modelos de Linguagem (como o ChatGPT ou o Gemini) podem analisar a descrição de uma vaga e sugerir quais palavras-chave você deve incluir no seu currículo para passar pelos filtros ATS.
  2. Preparação para Entrevistas: É possível treinar para entrevistas pedindo a uma IA que atue como um recrutador rigoroso, gerando perguntas comportamentais com base no seu cargo e avaliando as suas respostas.
  3. Cartas de Apresentação Personalizadas: A IA pode ajudar a redigir e estruturar cartas de apresentação altamente direcionadas para a cultura de uma empresa específica em questão de minutos.

O Fator Humano Ainda Importa?

Com tanta automação, é comum o medo de que o processo se torne frio e totalmente mecanizado. No entanto, o efeito tem sido o oposto nas etapas finais. Como a IA cuida da triagem técnica e da burocracia, os recrutadores humanos têm mais tempo para focar nas Soft Skills (habilidades comportamentais).

Empatia, inteligência emocional, capacidade de adaptação e pensamento crítico são características que os algoritmos ainda não conseguem medir com perfeição. Portanto, a regra de ouro para a procura de empregos na era da IA é: otimize o seu perfil para os robôs, mas encante os humanos.


Este conteúdo foi gerado para ajudar profissionais de Tech, Design e Marketing a navegarem no mercado de trabalho moderno. Encontre oportunidades incríveis em nossa plataforma.