Machine Learning Engineer, Senior Manager

Salary: $209,000 - 262,400 per year Requirements: We require a bachelors degree or higher in Computer Science, Machine Learning, or a related quantitative discipline such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering. We require at least 6 years of programming experience with Python, Java, Golang, or C++. We require at least 6 years of machine learning experience using industry-standard frameworks such as PyTorch or TensorFlow, along with libraries like Pandas, NumPy, and Scikit-learn. We require at least 6 years of experience working with large-scale distributed systems such as Spark or Ray to prepare AI/ML data. We require at least 4 years of experience deploying and operating machine learning solutions in production and running cloud-based services in AWS, GCP, or Azure, including Kubernetes for large-scale containerized ML systems. Preferred: a masters or doctoral degree in computer science, electrical engineering, mathematics, or a related field. Preferred: 5+ years of experience optimizing ML algorithms, configurations, and infrastructure. Preferred: 5+ years of experience applying software development best practices, including source control, testing, code reviews, and CI/CD. Preferred: 5+ years of experience building resilient software with pre-production testing, advanced deployment strategies, monitoring, alarms, and incident response planning. Preferred: 5+ years of experience with machine learning techniques, model types, architectures, training concepts, and model evaluation/debugging. Preferred: 5+ years of experience designing, implementing, and scaling production-ready data pipelines for ML training and evaluation. Preferred: demonstrated industry impact through conference presentations, papers, blog posts, open-source contributions, or patents. Preferred: the ability to explain complex technical and machine learning concepts clearly to varied audiences. Responsibilities: We design, build, and deliver machine learning models and components that address real business problems in partnership with Product and Data Science teams. We build and scale multi-tenant platforms that support large-scale model training and serving. We make ML infrastructure decisions informed by modeling techniques, data selection, feature engineering, training, hyperparameter tuning, dimensionality, bias/variance, and validation. We solve complex problems by writing and testing application code, developing and validating ML models, and automating testing and deployment. We work within cross-functional Agile teams to create and improve software for big data and machine learning applications. We retrain, maintain, and monitor models in production. We leverage or develop cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale. We build efficient data pipelines to supply ML models. We apply continuous integration and continuous deployment practices, including test automation and monitoring, to support reliable model and application releases. We ensure code is well managed to reduce vulnerabilities, keep models governed from a risk perspective, and follow Responsible and Explainable AI best practices. We use programming languages such as Python, Scala, or Java. Technologies: AI AWS Azure Big Data CI/CD Cloud GCP Golang Support Java Kubernetes Machine Learning Model Training PyTorch Python Scala Spark TensorFlow numpy pandas More: We are Risk Tech, where we build the data-driven foundation that helps Capital One operate in an uncertain world by transforming risk management with technology. Our team develops machine learning solutions that prevent risks and detect issues before they affect our customers, our business, or our communities. In this role, we partner with our GRC team and colleagues across the company to build and deploy proprietary AI-powered risk management solutions. We offer a fast-paced, collaborative, inclusive, and iterative environment, along with comprehensive benefits, performance-based incentives, and salary ranges that vary by location. This role may also include consideration for employment sponsorship where applicable. last updated 39 week of 2026