资深机器学习工程师
Staff Machine Learning Engineer
关于Nu
Nu是拉丁美洲领先的数字银行，为巴西、墨西哥和哥伦比亚的1.4亿客户提供服务。该公司通过利用数据和专有技术，开发创新产品和服务，引领行业变革。
以对抗复杂性、赋能人们为使命，Nu为客户提供完整的金融旅程，通过负责任的贷款和透明度促进金融准入和进步。公司由高效且可扩展的商业模式驱动，结合低成本服务与不断增长的回报。
Nu的影响已获得多项奖项的认可，包括《时代》100家最具影响力公司、《快公司》最具创新力公司以及《福布斯》全球最佳银行。
访问我们的机构页面 https://www.nu.com/2026-en
关于该职位
在AI核心团队，我们正在扩大AI项目的影响力，成为Nubank最关键决策系统的主要驱动力。我们正在寻找机器学习工程师，领导高影响力的科研项目，弥合最先进AI与生产级金融系统之间的差距。您将负责使用深度学习和基础模型解决复杂、模糊的问题，确保我们的架构具备可扩展性、高效性，并推动可衡量的业务成果。
作为机器学习工程师（MLE），您需要：
1. 研究执行与技术领导（复杂性与自主性）
- 独立领导并执行复杂的应用研究项目，专注于构建和优化架构（例如，Transformer、GNN），这些架构可以部署在信用、推荐系统、生成式AI和实时推理等关键用例中。
- 解决需要跨多个利益相关者（数据、基础设施、产品）协调的困难和模糊建模问题，交付具有明确中期影响的创新解决方案。
- 通过设计符合MLOps约束的架构，弥合研究与生产之间的差距，确保模型在延迟、可解释性和成本效率方面得到优化。
1. 战略影响与协作（影响）
- 开发并交付解决项目级挑战的创新方案，专注于将最新的平台和AI研究成果引入下游生产模型。
- 积极参与跨职能协作，确保研究成果无缝集成到Nubank的决策系统中。
查看英文原文
ABOUT NU
Nu is the leading digital bank in Latin America, serving 140 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
ABOUT THE ROLE
At AI Core, we are scaling the impact of our AI initiatives to become the primary driver of Nubank’s most critical decision systems. We are seeking Machine Learning Engineers to lead high-impact research projects that bridge the gap between state-of-the-art AI and production-grade financial systems. You will be responsible for solving complex, ambiguous problems using Deep Learning and Foundation Models, ensuring our architectures are scalable, efficient, and driving measurable business results.
As an Machine Learning Engineer (MLE), you’re expected to:
1. Research Execution & Technical Leadership (Complexity & Autonomy)
- Lead and execute complex applied research initiatives independently, focusing on building and optimizing architectures (e.g., Transformers, GNNs) that can be deployed across critical use cases like Credit, RecSys, GenAI, and real-time inference.
- Address difficult and ambiguous modeling problems that require coordination across various stakeholders (Data, Infra, Product), delivering innovative solutions with a clear focus on medium-term impact.
- Bridge the gap between research and production by designing architectures that respect MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-efficiency.
1. Strategic Impact & Collaboration (Impact)
- Develop and deliver innovative solutions that address project-level challenges, focusing on pushing the latest platform and AI research improvements into downstream production models.
- Actively participate in cross-functional collaborations, ensuring that research outputs are seamlessly integrated into Nubank's decision-making engines.
- Establish technical standards within the AI Core team for experimentation, model evaluation, and code quality, inspiring peers to raise their performance.
1. Mentorship & Function Contribution (Function Contribution)
- Serve as a technical mentor for senior engineers and researchers, providing guidance on deep learning fundamentals, problem formulation, and research methodology.
- Actively contribute to the function's growth by participating in mandatory activities like hiring (interview panels) and leading internal task forces to improve our ML lifecycle.
- Contribute to thought leadership by participating in research collaborations or internal papers that align with Nubank’s strategic goals.
What are we looking for?
- Professional Experience: 5-7+ years in applied AI/ML, with a proven track record of delivering research-driven systems into production environments
- Technical Mastery:
- Deep expertise in Deep Learning architectures (Transformers, Multimodal, or GNNs).
- Strong coding skills in Python and proficiency with frameworks like PyTorch, JAX, or TensorFlow.
- Solid understanding of MLOps and the constraints of deploying models at scale.
- Problem Solving: Sophisticated skills in ML problem formulation and the ability to navigate uncertainty when data is messy or unavailable.
- Communication: Ability to communicate complex technical concepts to both technical peers and cross-functional stakeholders, ensuring alignment and buy-in.
- Analytical Capacity: Experience with large-scale experimentation and A/B testing to validate research hypotheses.
Our Benefits
- Opportunity of earning equity at Nu
- Total compensation includes base salary, RSUs and benefits. Base salary range: $230k - $345k
- 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
- Extended maternity and paternity leaves
- 401K
- Saving Plans - Health Saving Account and Flexible Spending Account
- Work-from-home Allowance
- Relocation Assistance Package, if applicable.
Role Location
Palo Alto, California
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/
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.