Nubank

<h2>About Nu</h2>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<a target="_blank" rel="noopener noreferrer ugc" href="https://www.nu.com/2026-en"> Institutional Page</a>We're looking for a Staff Machine Learning Engineer to help lead the technical direction of our recommendation systems. This is a hands-on senior individual contributor role for someone who has shipped ML systems at scale before and wants to shape how Nubank builds them going forward.You'll be a technical anchor for the team, working on problems like retrieval, ranking and multi-objective optimization pipelines, and the infrastructure that lets these systems serve millions of customers with low latency and high reliability.You'll be responsible for<ul><li>Setting technical direction for recommendation systems, including architecture decisions that other engineers will build on for years.</li><li>Designing and building production ML systems for retrieval, ranking, and multi-objective optimization that operate at scale and under real latency constraints. You will be hands-on, regularly making coding contributions.</li><li>Leading the most technically demanding projects on the team, from first design through production rollout.</li><li>Partnering with applied scientists to move models from research into reliable, monitored production systems.</li><li>Raising the technical bar for the team: reviewing designs, mentoring engineers, and pushing for better practices around testing, experimentation, monitoring, and system design.</li><li>Working directly with stakeholder teams to understand their recommendation needs and translate them into shared, reusable infrastructure rather than one-off solutions.</li><li>Identifying and fixing the structural issues that slow the team down, whether that's tooling, process, or technical debt.</li></ul>We're looking for someone who has<ul><li>A strong track record building and operating large-scale ML systems in production, ideally recommendation, ranking, or personalization systems.</li><li>Experience building modern recommendation systems, e.g., learned embeddings, semantic IDs, sequence models over long user histories, and conversational recommendation systems.</li><li>Deep experience with the full ML engineering lifecycle: training, deployment, monitoring, data consistency, experimentation, and governance.</li><li>Strong software engineering fundamentals and fluency in Python and/or Scala, or equivalent languages.</li><li>Real experience with the operational side of ML: on-call, incident response, debugging systems under load.</li><li>A track record of technical leadership, whether that's an official title or just being the person a team leans on for the hard calls.</li><li>Comfort working with ambiguity and translating loose business goals into concrete technical priorities.</li><li>Good communication skills. You'll need to explain technical tradeoffs to both engineers and non-technical stakeholders.</li><li>Experience with distributed systems, Spark, or similar large-scale data processing tools is a plus. Our Benefits<ul><li>Opportunity of earning equity at Nu</li><li>Total compensation includes base salary, RSUs and benefits. Base salary range: $230k - $345k</li><li>Medical Insurance</li><li>Dental and Vision Insurance</li><li>Life Insurance and AD&amp;D</li><li>Extended maternity and paternity leaves </li><li>Nucleo - Our learning platform of courses</li><li>NuLanguage - Our language learning program</li><li>NuCare - Our mental health and wellness assistance program</li><li>Extended maternity and paternity leaves </li><li>401K</li><li>Saving Plans - Health Saving Account and Flexible Spending Account</li><li>Work-from-home Allowance</li><li>Relocation Assistance Package, if applicable.</li></ul>Role LocationPalo 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 <a target="_blank" rel="noopener noreferrer ugc" href="https://building.nubank.com/nu-hybrid-work-model/">https://building.nubank.com/nu-hybrid-work-model/</a> </li></ul>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.

Staff Machine Learning Engineer, Recommendation Systems

<h2>About Nu</h2>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<a target="_blank" rel="noopener noreferrer ugc" href="https://www.nu.com/2026-en"> Institutional Page</a><h3> About the role</h3>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:<ol><li>Research Execution &amp; Technical Leadership (Complexity &amp; Autonomy)</li></ol><ul><li>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.</li><li>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.</li><li>Bridge the gap between research and production by designing architectures that respect MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-efficiency.</li></ul><ol><li>Strategic Impact &amp; Collaboration (Impact)</li></ol><ul><li>Develop and deliver innovative solutions that address project-level challenges, focusing on pushing the latest platform and AI research improvements into downstream production models.</li><li>Actively participate in cross-functional collaborations, ensuring that research outputs are seamlessly integrated into Nubank's decision-making engines.</li><li>Establish technical standards within the AI Core team for experimentation, model evaluation, and code quality, inspiring peers to raise their performance.</li></ul><ol><li>Mentorship &amp; Function Contribution (Function Contribution)</li></ol><ul><li>Serve as a technical mentor for senior engineers and researchers, providing guidance on deep learning fundamentals, problem formulation, and research methodology.</li><li>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.</li><li>Contribute to thought leadership by participating in research collaborations or internal papers that align with Nubank’s strategic goals.</li></ul>What are we looking for?<ul><li>Professional Experience: 5-7+ years in applied AI/ML, with a proven track record of delivering research-driven systems into production environments</li><li>Technical Mastery:<ul><li>Deep expertise in Deep Learning architectures (Transformers, Multimodal, or GNNs).</li><li>Strong coding skills in Python and proficiency with frameworks like PyTorch, JAX, or TensorFlow.</li><li>Solid understanding of MLOps and the constraints of deploying models at scale.</li></ul></li><li>Problem Solving: Sophisticated skills in ML problem formulation and the ability to navigate uncertainty when data is messy or unavailable.</li><li>Communication: Ability to communicate complex technical concepts to both technical peers and cross-functional stakeholders, ensuring alignment and buy-in.</li><li>Analytical Capacity: Experience with large-scale experimentation and A/B testing to validate research hypotheses.</li></ul>Our Benefits<ul><li>Opportunity of earning equity at Nu</li><li>Total compensation includes base salary, RSUs and benefits. Base salary range: $230k - $345k</li><li>Medical Insurance</li><li>Dental and Vision Insurance</li><li>Life Insurance and AD&amp;D</li><li>Extended maternity and paternity leaves </li><li>Nucleo - Our learning platform of courses</li><li>NuLanguage - Our language learning program</li><li>NuCare - Our mental health and wellness assistance program</li><li>Extended maternity and paternity leaves </li><li>401K</li><li>Saving Plans - Health Saving Account and Flexible Spending Account</li><li>Work-from-home Allowance</li><li>Relocation Assistance Package, if applicable.</li></ul>Role LocationPalo 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 <a target="_blank" rel="noopener noreferrer ugc" href="https://building.nubank.com/nu-hybrid-work-model/">https://building.nubank.com/nu-hybrid-work-model/</a> 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.

Staff Machine Learning Engineer

<h2>About Nu</h2>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<a target="_blank" rel="noopener noreferrer ugc" href="https://www.nu.com/2026-en"> Institutional Page</a> About the RoleAt Nu, data is the foundation that powers our AI and machine learning models, enabling millions of customers to access fair financial products. As a Machine Learning Engineer in AI Core, Data Intelligence, you’ll work across a broad spectrum — from building scalable data infrastructure and feature pipelines that feed our state-of-the-art foundation models to designing, training, and shipping transaction classification models that power critical customer experiences across the company.You'll work at the intersection of data and applied machine learning, contributing across multiple stages of the ML lifecycle: ingesting and labeling data, training and evaluating models, and helping with deployment and production monitoring through robust quality controls. You’ll partner closely with product, compliance, and ML teams to ensure models are auditable, privacy-aware, and deliver measurable business value.You'll join a team that manages the data engineering backbone of AI Core, ensuring data is accessible, healthy, and properly tracked across our entire ML ecosystem. Here, you'll combine your expertise in building scalable data systems with your passion for machine learning, creating solutions that enable our models to learn from better, richer data.You can read more about the work in the AI Core team on our blog: <a target="_blank" rel="noopener noreferrer ugc" href="https://building.nubank.com/understanding-our-customers-finances-through-foundation-models/">https://building.nubank.com/understanding-our-customers-finances-through-foundation-models/</a>Key ResponsibilitiesAs a Lead Machine Learning Engineer in AI Core Data Intelligence, you will:<ul><li>Design and build scalable data ingestion pipelines that bring new datasets into our AI Core platform, ensuring reliable, efficient data flow from source to model training.</li><li>Implement data quality monitoring and validation systems that catch issues before they impact model performance, maintaining the health of datasets across our ML ecosystem.</li><li>Model new types of data into our foundation models.</li><li>Analyze the impact of new data sources on existing models, conducting experiments to measure performance improvements and guide data acquisition decisions.</li><li>Develop and maintain data preparation workflows that transform raw data into features ready for model training, working with distributed computing frameworks like Ray.</li><li>Tune and optimize machine learning models when new datasets are integrated, applying hyperparameter optimization and evaluating model performance improvements.</li><li>Collaborate with AI Core ML, Platform, and Infra teams to ensure seamless data flow across our ML infrastructure, from ingestion to model deployment.</li><li>Lead technical initiatives that improve our data engineering practices, setting standards for data quality, pipeline reliability, and model-data integration.</li><li>Mentor team members and contribute to hiring activities, helping build a strong and diverse team that drives innovation in AI infrastructure.</li></ul>Basic Qualifications<ul><li>Typically 6+ years of experience in machine learning engineering, data engineering, or related fields with a strong track record of building production data and ML systems.</li><li>Proven experience designing and building data ingestion pipelines at scale, with expertise in distributed computing frameworks (Ray, Spark, or similar).</li><li>Strong background in applied machine learning, including model training, hyperparameter tuning, and performance evaluation.</li><li>Experience analyzing how data changes impact model performance, with the ability to design and run experiments to measure improvements.</li><li>Proficiency in Python for data engineering and ML workflows, with experience working with large-scale data processing systems.</li><li>Solid understanding of data quality principles and experience implementing monitoring, validation, and alerting systems.</li><li>Strong problem-solving skills with the ability to address complex, ambiguous problems requiring coordination across multiple teams.</li><li>Excellent communication skills, capable of explaining technical concepts to both technical and non-technical stakeholders.</li><li>Demonstrated leadership experience, including mentoring team members and contributing to technical decision-making.</li></ul>Preferred Qualifications<ul><li>Experience with MLflow or similar model tracking and versioning systems.</li><li>Knowledge of foundation models, fine-tuning workflows, and transformer architectures.</li><li>Experience with data pipeline orchestration tools (Dagster, Airflow, or similar).</li><li>Background in financial services or fintech, understanding the unique data challenges in this domain.</li><li>Experience working in a fast-paced, high-growth environment with distributed teams.</li><li>Track record of reducing complexity in data systems and improving developer experience for ML teams. </li></ul>Our Benefits<ul><li>Opportunity of earning equity at Nu</li><li>Medical Insurance</li><li>Dental and Vision Insurance</li><li>Life Insurance and AD&amp;D</li><li>Extended maternity and paternity leaves </li><li>Nucleo - Our learning platform of courses</li><li>NuLanguage - Our language learning program</li><li>NuCare - Our mental health and wellness assistance program</li><li>Extended maternity and paternity leaves </li><li>401K</li><li>Saving Plans - Health Saving Account and Flexible Spending Account</li><li>Work-from-home Allowance</li><li>Relocation Assistance Package, if applicable.</li></ul><h3>Work Model for this Role</h3>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 <a target="_blank" rel="noopener noreferrer ugc" href="https://building.nubank.com/nu-hybrid-work-model/">https://building.nubank.com/nu-hybrid-work-model/</a>Locations: This role is available in any of our North American offices (Palo Alto, USA; Miami, USA; Durham, USA; Toronto, CAN)<div> </div><div> </div>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.

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Staff Machine Learning Engineer, Recommendation Systems

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