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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) - **Company:** Capital One Financial Corporation - **Location:** San Francisco, CA, United States - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Algorithm Design, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Big Data, C++ (Programming Language), Cluster Analysis, Code Review, Computer Programming, Continuous Delivery, Continuous Integration, Information Engineering, Distributed Systems, High-Level Architecture, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Software Systems, SQL Databases, Reinforcement Learning, Software Organization, Dial-Up, Google Cloud, Pytorch, Apache Spark, Pandas, Scikit Learn, Kubernetes, Information Technology, Feature Selection, Machine Learning Operations, Software Version Control, Data Pipelines, Golang, Programming Languages - **Published:** September 24, 2026 - **Apply:** https://dejobs.org/x/x/68FB3BD5AD08431799B22EB393675E17/job/ ## About the Role * Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) * At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) * At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data * At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems, * Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field * 3+ years of experience optimizing ML algorithms, configurations, and infrastructure * 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. * 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. * 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) * 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. * 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation * Authored/co-authored a paper on a ML technique, model, or proof of concept ## Description Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. What You'll Do: * The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: * Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams * Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) * Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment * Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications * Retrain, maintain, and monitor models in production * Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale * Construct optimized data pipelines to feed ML models * Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code * Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI * Use programming languages like Python, Scala, or Java ## Related Videos - [Vectorize all the things! 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