Machine Learning Engineer at Nubank | Palo Alto

NubankUSA, Palo Alto

On-site Full-time

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Experience Level

Experience

Qualifications

Qualifications Proven experience in developing and deploying machine learning models in production environments. Strong understanding of Deep Learning frameworks and techniques. Familiarity with MLOps practices and tools. Ability to collaborate effectively with cross-functional teams. Excellent problem-solving skills and a proactive mindset.

About the job

Join Our Innovative Team

Nubank is a leading digital financial platform, serving over 122 million customers across Brazil, Mexico, and Colombia. Our mission is to simplify financial services and empower individuals, marking the start of a vibrant future in Latin America.

As a publicly listed company on the New York Stock Exchange (NYSE: NU), we leverage cutting-edge technology and data intelligence to create financial products that are not only accessible but also user-friendly.

Our achievements have earned us recognition from prestigious rankings, such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Explore more about us on our institutional page here.

About the Role

At AI Core, we are expanding our AI initiatives to become the backbone of Nubank's key decision-making systems. We are in search of talented Machine Learning Engineers to spearhead impactful research projects that connect advanced AI technologies with real-world financial systems. Your role will involve tackling intricate challenges using Deep Learning and Foundation Models, ensuring our solutions are scalable, efficient, and yield tangible business outcomes.

As a Machine Learning Engineer (MLE), your responsibilities will include:

Leading and executing complex applied research initiatives independently, focusing on building and optimizing architectures (e.g., Transformers, GNNs) for critical applications such as Credit, Recommendation Systems, Generative AI, and real-time inference.
Resolving challenging and ambiguous modeling problems that necessitate collaboration across various teams (Data, Infrastructure, Product), delivering innovative solutions with a clear emphasis on medium-term impact.
Connecting the research and production worlds by designing architectures that comply with MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-effectiveness.

We invite you to be part of our journey to revolutionize the financial landscape.

About Nubank

Nubank is one of the largest digital financial platforms globally, committed to simplifying financial services and making them more accessible to customers across Latin America. With a strong focus on technology and innovation, we aim to create a positive impact in the financial industry.

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Jan 27, 2026

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Machine Learning Engineer at Nubank | Palo Alto

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Full-time|On-site|USA, Palo Alto

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Mar 18, 2026

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Machine Learning / AI Software Engineering Internship

Pathwaycom

Internship|On-site|Palo Alto, California, United States

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Jul 18, 2025

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Engineering Manager for Machine Learning in Behavior Planning & Prediction

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Full-time|On-site|Palo Alto, CA

Woven by Toyota is at the forefront of Toyota’s groundbreaking transition into a mobility enterprise. With a commitment to innovating for the greater good, our mission is to revolutionize mobility through human-centric advancements that redefine its meaning and societal impact.Our initiatives are built upon four foundational pillars: AD/ADAS, encompassing our autonomous driving and advanced driver assistance technologies; Arene, our software development platform tailored for software-defined vehicles; Woven City, a pioneering testbed for mobility innovations; and Cloud & AI, the digital backbone that supports our collaborative framework. Our business-critical functions empower these teams to collaborate effectively in pursuit of a singular, ambitious goal: to create a world devoid of accidents and enhance the well-being of all.Team OverviewThe Behavior team at Woven by Toyota addresses autonomous challenges related to prediction and trajectory planning. Our work encompasses an array of tasks, including the analysis of petabytes of multimodal driving data, optimization problem-solving, latency reduction on hardware accelerators, deployment of scalable and efficient machine learning (ML) training and evaluation pathways, and the design of innovative neural network architectures to push the boundaries of ML in Prediction and Motion Planning.Candidate ProfileWe are searching for a highly experienced, technically adept Engineering Manager to spearhead a team of talented engineers within the behavior group. This role emphasizes the development and implementation of cutting-edge machine learning models for planning and prediction in AD/ADAS, alongside their related data processing frameworks and vehicle integration. The ideal candidate should possess a profound enthusiasm for self-driving technology and its transformative potential on a global scale. You will guide your team in enhancing our core behavior machine learning models and associated pipelines. We seek an individual with deep expertise in machine learning, a thorough comprehension of the model lifecycle, and substantial experience in creating tools and pipelines to address behavioral challenges. Success in this role necessitates a candidate who flourishes in a dynamic environment, is hands-on, and is driven to expand the frontiers of our technology. Prior experience in developing and deploying real-world autonomous driving products and collaborating with exceptionally skilled engineers is crucial.

Feb 27, 2026

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Senior Software Engineer - Machine Learning Offboarding Models

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Full-time|On-site|Palo Alto, CA

Join our innovative team at latitude as a Senior Software Engineer specializing in Machine Learning Offboarding Models. In this role, you will leverage your expertise in software engineering and machine learning to develop robust models that enhance our offboarding processes. Your contributions will directly impact our operational efficiency and improve user experiences.As a key member of our team, you will collaborate with cross-functional teams to design, implement, and optimize machine learning solutions. We seek a passionate engineer who thrives in a fast-paced environment and is eager to tackle challenging problems.

Mar 17, 2026

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Machine Learning Engineer at Nace.AI | Palo Alto, CA

Nace.AI

Full-time|On-site|Palo Alto, CA

Role Overview:Join Nace.AI as a Machine Learning Engineer, where you will be instrumental in transforming advanced machine learning research into scalable, production-ready applications. Collaborating with interdisciplinary teams, you will pinpoint areas where machine learning can enhance product offerings, design robust model-centric architectures, and guarantee their smooth integration into practical applications. This role demands a harmonious blend of theoretical insight and hands-on engineering, focusing on creating dependable, maintainable, and impactful AI-driven features that align with Nace.AI's strategic goals.Key Responsibilities:Develop and sustain complete ML systems, including synthetic data pipelines, model training, debugging, and performance assessment.Enhance large language models (LLMs) and utilize meta-learning strategies to boost model generalization and efficiency.Refine existing Nace.AI models by integrating breakthroughs from the latest ML research.

Mar 17, 2026

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Principal Machine Learning Engineer - Training Systems

Rhoda AI

Full-time|On-site|Palo Alto

At Rhoda AI, we are pioneering the development of a comprehensive foundation for the next generation of humanoid robots. Our focus spans high-performance, software-defined hardware to advanced foundational models and video world models that govern robot functionality. Our robots are engineered to be versatile, capable of navigating intricate, real-world environments and tackling scenarios not previously encountered in training. We stand at the crossroads of large-scale learning, robotics, and systems, bolstered by a research team comprising experts from prestigious institutions such as Stanford, Berkeley, and Harvard. Our ambition is not merely to add features; we are crafting a revolutionary computing platform for physical tasks, underpinned by over $400 million in funding, driving aggressive investments in research & development, hardware innovation, and scaling up manufacturing to bring our vision to fruition.Role OverviewWe are in search of a Principal Machine Learning Systems Engineer to take charge of our training systems' performance from start to finish. You will be instrumental in defining the scaling of our model training, enhancing efficiency, scalability, and accuracy across extensive multimodal training environments. This is a pivotal systems role, not merely focused on infrastructure support. Your contributions will significantly influence our compute utilization efficiency, scalability of models across thousands of GPUs, and the speed of research iterations.Your ResponsibilitiesOversee training performance from start to finishAnalyze and enhance the performance of large-scale multimodal training encompassing vision, video, proprioception, actions, and language.Create systematic performance attributions by breaking down step-time into compute, communication, and input pipeline, along with scaling curves for various cluster sizes and identifying key bottlenecks.Drive quantifiable improvements across:Distributed efficiency (e.g., communication and compute overlap, bucketization, topology-aware mapping, and parallelism strategies).Compute efficiency (e.g., identifying kernel hotspots, operator fusion, attention optimization, and minimizing framework/runtime overhead).Memory efficiency (e.g., activation checkpointing, sequence packing, and reducing fragmentation).Design training systems rather than just tuning themDefine and refine parallelism strategies including data, tensor, pipeline, sharding, and hybrid approaches.Enhance execution efficiency through communication scheduling, graph capture, execution optimization, and runtime enhancements.Contribute to the overall system architecture with innovative solutions.

Mar 10, 2026

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