Machine Learning Engineer (Python, AWS)

Salary: $179,400 - 245,600 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 4 years of programming experience with Python, Java, Golang, or C++. We require at least 4 years of machine learning experience using standard frameworks such as PyTorch or TensorFlow, along with libraries like Pandas, NumPy, and Scikit-learn. We require at least 4 years of experience working with large-scale distributed systems such as Spark or Ray to prepare AI/ML data. We require at least 2 years of experience deploying and operating machine learning solutions in production and running cloud-based production services on AWS, GCP, or Azure, including Kubernetes for large-scale containerized ML systems. Preferred qualifications include a masters or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field. Preferred experience includes 3+ years optimizing ML algorithms, configurations, and infrastructure. Preferred experience includes 3+ years following software development best practices such as source control, testing, code reviews, and CI/CD. Preferred experience includes 3+ years building resilient software solutions with pre-production testing, advanced deployment methods, monitoring, alerts, and incident response planning. Preferred experience includes 3+ years working with ML techniques, model types, architectures, training concepts, and model evaluation/debugging. Preferred experience includes 3+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. Preferred experience includes 1+ years serving as a technical lead for ML solutions using best practices, patterns, and automation. Preferred qualifications include having authored or co-authored a paper on an ML technique, model, or proof of concept. Responsibilities: We design, build, and deliver ML models and components that solve real business problems in partnership with Product and Data Science teams. We use our understanding of ML modeling techniques to guide infrastructure decisions, including model choice, data and feature selection, 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 tests and deployment. We collaborate on cross-functional Agile teams to build and enhance software for advanced big data and ML applications. We retrain, maintain, and monitor models in production. We leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale. We construct efficient data pipelines to feed ML models. We apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful deployment of ML models and application code. We ensure code is well-managed to reduce vulnerabilities, models are properly governed from a risk perspective, and our ML work follows 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 Marketing PyTorch Python Scala Spark TensorFlow numpy pandas Model Training SQL More: We are Capital Ones Enterprise Platforms Technology organization, and our Marketing and Messaging team builds scalable platforms that deliver hyper-personalized omnichannel messages and experiences across owned and paid Adtech channels to delight customers, attract prospects, and drive business value. This Machine Learning Engineer 4 role sits within a fast-paced, collaborative, inclusive, and iterative environment focused on pioneering AI transformations and scaling production models. The position offers a competitive salary range that varies by location, performance-based incentive compensation, and a comprehensive benefits package supporting health, financial, and overall well-being. The role is available in locations including McLean, New York, Plano, Richmond, and San Francisco, and applications are accepted for a minimum of 5 business days. last updated 39 week of 2026