Nubank

<h2>About Nu</h2>Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.<div> </div>Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. Visit our<a target="_blank" rel="noopener noreferrer ugc" href="https://www.nu.com/2026-en"> Institutional Page</a><h2>About the Program</h2>The Nu AI Core Summer Internship Program is a research-focused internship for PhD students working at the frontier of artificial intelligence and machine learning.Over about 12 weeks, interns collaborate with engineers, applied scientists, and researchers on complex AI challenges. Each intern leads an end-to-end research or applied AI project that combines research methods with large-scale production environments.The program builds long-term relationships between industry and academia and with emerging AI research talent.<h2> Program Structure</h2><ul><li>Duration: ~12 weeks</li><li>Start dates: May–June, aligned with US university calendars</li><li>Location model: Remote, with one in-person week at Nu's Palo Alto office in Silicon Valley, fully covered by us.</li></ul>What you get<ul><li>Dedicated research mentor</li><li>Ownership of a scoped AI research project</li><li>Access to large-scale datasets and compute infrastructure</li><li>Research talks and technical seminars</li><li>Final research presentation to leadership and AI teams</li></ul><h2>Research Areas</h2>Interns may work on projects related to:<ul><li>Machine learning and deep learning</li><li>Large language models and generative AI</li><li>Recommender systems and ranking models</li><li>AI infrastructure and model optimization</li><li>Responsible AI and model evaluation</li></ul>Projects typically combine research experimentation with applied system development, including model design, experimentation, and large-scale evaluation.<h2> Candidate Profile</h2>This program targets PhD students conducting research in AI and machine learning who are interested in applying their work to real-world systems.Applicants are typically pursuing a PhD in fields such as:<ul><li>Computer Science</li><li>Machine Learning</li><li>Artificial Intelligence</li><li>Statistics</li><li>Mathematics</li><li>Computational Linguistics</li><li>Electrical Engineering</li><li>or related quantitative disciplines.</li></ul><h2> Basic Qualifications (Application/ Screening Filters)</h2><ul><li>Currently enrolled in a PhD program</li><li>Research focus in machine learning, AI, statistics or related areas</li><li>Strong programming skills in Python or similar languages</li><li>Experience working with machine learning frameworks (e.g., PyTorch, TensorFlow)</li><li>Experience designing experiments and evaluating models</li><li>Experience working with large datasets or training ML models </li></ul><h2>Preferred Qualifications</h2>Strong candidates may also demonstrate:<ul><li>Publications at top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, KDD, RecSys, CVPR, CIKM or equivalent-conferences for related fields)</li><li>Experience working with large-scale ML systems or distributed training</li><li>Experience with LLMs, generative AI, or foundation models</li><li>Open-source contributions in AI or ML</li><li>Experience collaborating in interdisciplinary research environments</li></ul><h2> What We Value</h2>We are particularly interested in candidates who demonstrate:<ul><li>Strong research rigor and experimental methodology</li><li>Ability to translate research ideas into practical systems</li><li>Track record of identifying novel research directions or reframing existing problems</li><li>Intellectual curiosity and independent problem solving</li><li>Collaboration with engineers and cross-functional teams</li><li>Interest in deploying AI systems with real-world impact</li><li></li></ul><h2>Benefits</h2><ul><li>Top Tier Medical Insurance</li><li>Top Tier 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>401K</li><li>Saving Plans - Health Saving Account and Flexible Spending Account</li></ul><h2> Location for this opportunity</h2>Remote, but only for USA PhD students<h2></h2>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. To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works <a target="_blank" rel="noopener noreferrer ugc" href="https://script.google.com/a/macros/nubank.com.br/s/AKfycbwvrewE58oGSbRWIVv8CyCWN68GLxpPVsfYYXv-ZHg94QFsTJmi82rF1x0yt-OTs2W0DQ/exec">here</a>

Nu AI Core Summer PhD Research Internship

<h2>About Nu</h2>Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.<div> </div>Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. Visit our<a target="_blank" rel="noopener noreferrer ugc" href="https://www.nu.com/2026-en"> Institutional Page</a><h2>Machine Learning Engineer at Nubank</h2>At Nubank, Machine Learning Engineers sit at the core of how we make decisions at scale. We build, train, and deploy models that drive credit, fraud, risk, personalization decisions and a growing set of AI-native experiences for millions of customers every day. We do it with engineering rigor, statistical depth, and a deep focus on impact.Our MLEs work across the full modeling lifecycle: framing business problems as ML problems, engineering features, training and validating models, and deploying and monitoring them in production. We value small, independent teams that move fast, own their decisions end-to-end, and hold themselves to a high bar for quality and craft.Increasingly, that work also includes Generative AI and Agentic Engineering. Depending on the problem, our engineers design and build systems that combine models, tools, workflows, evaluation loops, and human oversight to solve real business tasks reliably in production.We strive for state-of-the-art ML practices that currently include a variety of technologies. While we value candidates that are familiar with them, we are also confident that engineers who are interested in joining Nubank will be able to learn from our team. <ul><li>Large-scale model training and experimentation pipelines</li><li>Feature engineering and feature stores feeding both batch and real-time models</li><li>Model deployment and serving in production, with monitoring through operational and business metrics</li><li>Distributed data processing for training datasets at scale</li><li>Continuous Integration and Deployment into AWS and Kubernetes</li><li>Experiment tracking, model versioning, and reproducibility tooling</li><li>A robust data platform built on modern ETL/ELT practices</li></ul><h3>As a Machine Learning Engineer, you’re expected to:</h3><ul><li>Directly contribute to Nu Colombia’s strategy and performance mainly by building forecasting models and models to assess and decide on marketing investments</li><li>Frame ambiguous business problems as well-defined modeling problems</li><li>Design, build and validate machine learning models, ensuring statistical rigor and business relevance</li><li>Engineer and maintain features and datasets used for training and inference</li><li>Deploy and maintain ML models in both batch and real-time scenarios, integrating them with other systems and monitoring through operational and business metrics</li><li>Lead modeling projects end-to-end — from problem framing and stakeholder alignment to delivery, monitoring and iteration</li><li>Translate business needs into modeling strategies aligned with Nubank's architecture and long-term goals </li></ul><h2>What We're Looking For</h2><ul><li>Strong foundation in statistics, machine learning theory and modeling techniques (e.g. regression, tree-based models, deep learning)</li><li>Programming experience in Python and familiarity with ML libraries (e.g. scikit-learn, PyTorch, TensorFlow, XGBoost)</li><li>Experience training, validating, and tuning models, with solid understanding of overfitting, bias-variance tradeoff and evaluation metrics</li><li>Understanding of the ML model lifecycle, from training and evaluation to deployment and monitoring</li><li>Ability to write efficient SQL queries and work with analytical data environments</li><li>Strong communication skills to collaborate with both technical and business stakeholders</li><li>Passion for building high-quality, production-grade models</li></ul><h2>Nice to Have</h2><ul><li>Experience with cloud platforms such as AWS, GCP or Azure</li><li>Familiarity with distributed systems, microservices and asynchronous architectures</li><li>Experience with feature stores, MLOps tooling and experiment tracking (e.g. MLflow, Feast, Airflow)</li><li>Knowledge of data architecture patterns (Data Lake, Data Warehouse, Data Mart)</li><li>Experience with data visualization tools (Looker, Power BI, Tableau or similar)</li><li>Knowledge of software engineering best practices: testing, clean code, documentation</li></ul><h2>Core Benefits</h2><ul><li>Chance of earning equity at Nu</li><li>Extended maternity and paternity leaves</li><li>Health and life insurance</li><li>NuCare - Our mental health and wellness assistance program</li><li>Nucleo - Our learning platform of courses</li><li>NuLanguage - Our language learning program</li><li>Vacations of 15 workdays</li><li>Gym partnership</li><li>Work-from-home Allowance</li><li>Parental Consultancy</li><li>Relocation Assistance Package, if applicable</li></ul><h2>Work Model</h2>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><h2>Role Location</h2>Bogota, Colombia.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. To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works <a target="_blank" rel="noopener noreferrer ugc" href="https://script.google.com/a/macros/nubank.com.br/s/AKfycbwvrewE58oGSbRWIVv8CyCWN68GLxpPVsfYYXv-ZHg94QFsTJmi82rF1x0yt-OTs2W0DQ/exec">here</a>

Senior Machine Learning Engineer

<h2>About Nu</h2>Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.<div> </div>Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. Visit our<a target="_blank" rel="noopener noreferrer ugc" href="https://www.nu.com/2026-en"> Institutional Page</a>Machine Learning Engineer at Nubank At Nubank, Machine Learning Engineers sit at the core of how we make decisions at scale. We build, train, and deploy models that drive credit, fraud, risk, personalization decisions and a growing set of AI-native experiences for millions of customers every day. We do it with engineering rigor, statistical depth, and a deep focus on impact.Our MLEs work across the full modeling lifecycle: framing business problems as ML problems, engineering features, training and validating models, and deploying and monitoring them in production. We value small, independent teams that move fast, own their decisions end-to-end, and hold themselves to a high bar for quality and craft.Increasingly, that work also includes Generative AI and Agentic Engineering. Depending on the problem, our engineers design and build systems that combine models, tools, workflows, evaluation loops, and human oversight to solve real business tasks reliably in production.We strive for state-of-the-art ML practices that currently include a variety of technologies. While we value candidates that are familiar with them, we are also confident that engineers who are interested in joining Nubank will be able to learn from our team. <ul><li>Large-scale model training and experimentation pipelines</li><li>Feature engineering and feature stores feeding both batch and real-time models</li><li>Model deployment and serving in production, with monitoring through operational and business metrics</li><li>Distributed data processing for training datasets at scale</li><li>Continuous Integration and Deployment into AWS and Kubernetes</li><li>Experiment tracking, model versioning, and reproducibility tooling</li><li>A robust data platform built on modern ETL/ELT practices</li></ul><h2>As a Machine Learning Engineer, you’re expected to:</h2><ul><li>Frame ambiguous business problems as well-defined modeling problems</li><li>Design, build and validate machine learning models, ensuring statistical rigor and business relevance</li><li>Engineer and maintain features and datasets used for training and inference</li><li>Deploy and maintain ML models in both batch and real-time scenarios, integrating them with other systems and monitoring through operational and business metrics</li><li>Lead modeling projects end-to-end — from problem framing and stakeholder alignment to delivery, monitoring and iteration</li><li>Contribute to the design, documentation, maintenance and optimization of our modeling codebase, platforms and tooling</li><li>Translate business needs into modeling strategies aligned with Nubank's architecture and long-term goals</li><li>Partner with technical and business stakeholders to define strategies and deliver high-impact models</li><li>Share knowledge, mentor peers and contribute to ML and data literacy initiatives across Nubank</li></ul><h2>What We're Looking For</h2><ul><li>Strong foundation in statistics, machine learning theory and modeling techniques (e.g. regression, tree-based models, deep learning)</li><li>Programming experience in Python and familiarity with ML libraries (e.g. scikit-learn, PyTorch, TensorFlow, XGBoost)</li><li>Experience training, validating, and tuning models, with solid understanding of overfitting, bias-variance tradeoff and evaluation metrics</li><li>Understanding of the ML model lifecycle, from training and evaluation to deployment and monitoring</li><li>Ability to write efficient SQL queries and work with analytical data environments</li><li>Strong communication skills to collaborate with both technical and business stakeholders</li><li>Passion for building high-quality, production-grade models</li></ul><h2>Nice to Have</h2><ul><li>Experience with cloud platforms such as AWS, GCP or Azure</li><li>Familiarity with distributed systems, microservices and asynchronous architectures</li><li>Experience with feature stores, MLOps tooling and experiment tracking (e.g. MLflow, Feast, Airflow)</li><li>Knowledge of data architecture patterns (Data Lake, Data Warehouse, Data Mart)</li><li>Experience with data visualization tools (Looker, Power BI, Tableau or similar)</li></ul>Knowledge of software engineering best practices: testing, clean code, documentation <h2>Our Benefits</h2><ul><li>Chance of earning equity at Nubank</li><li>Food/Meal Card (Vale-Refeição and/or Vale Alimentação)</li><li>Public Transportation Commuting Benefit (Vale-Transporte)</li><li>NuCare – Psychological, Financial and Legal Assistance Program</li><li>Life Insurance, Medical Plan and Dental Plan</li><li>NuLanguage – Language Course Program</li><li>Nucleo – Our learning platform</li><li>Extended Parental Leave, Daycare Allowance and Parental Consultancy</li><li>Work-from-home Allowance</li><li>Gym Partnerships</li><li>30 days of paid vacation</li><li>Relocation Assistance Package, if applicable</li></ul><h2>Work Model</h2>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="http://building.nubank.com/nu-hybrid-work-model/">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. To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works <a target="_blank" rel="noopener noreferrer ugc" href="https://script.google.com/a/macros/nubank.com.br/s/AKfycbwvrewE58oGSbRWIVv8CyCWN68GLxpPVsfYYXv-ZHg94QFsTJmi82rF1x0yt-OTs2W0DQ/exec">here</a>

Lead Machine Learning Engineer

<h2>About Nu</h2>Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.<div> </div>Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. 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. To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works <a target="_blank" rel="noopener noreferrer ugc" href="https://script.google.com/a/macros/nubank.com.br/s/AKfycbwvrewE58oGSbRWIVv8CyCWN68GLxpPVsfYYXv-ZHg94QFsTJmi82rF1x0yt-OTs2W0DQ/exec">here</a>

Staff Machine Learning Engineer, Recommendation Systems

<h2>About Nu</h2>Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.<div> </div>Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. 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. To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works <a target="_blank" rel="noopener noreferrer ugc" href="https://script.google.com/a/macros/nubank.com.br/s/AKfycbwvrewE58oGSbRWIVv8CyCWN68GLxpPVsfYYXv-ZHg94QFsTJmi82rF1x0yt-OTs2W0DQ/exec">here</a>

Nubank

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Nu AI Core Summer PhD Research Internship

Senior Machine Learning Engineer

Lead Machine Learning Engineer

Staff Machine Learning Engineer, Recommendation Systems

Staff Machine Learning Engineer

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