Machine Learning Engineer, Intelligent Foundations

Salary: $215,200 - 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 expect at least 4 years of programming experience with Python, Java, Golang, or C++ We require at least 4 years of machine learning experience using industry-standard frameworks such as PyTorch or TensorFlow and libraries including Pandas, NumPy, and Scikit-learn We expect 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 services in AWS, GCP, or Azure, including Kubernetes for large-scale containerized ML systems A masters or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field is preferred 3+ years of experience optimizing machine learning algorithms, configurations, and infrastructure is preferred 3+ years of experience applying software development best practices such as source control, testing, code reviews, and CI/CD is preferred 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment methods, monitoring, alarms, and incident response planning is preferred 3+ years of experience with machine learning methods, model types, architectures, training concepts, and model evaluation is preferred 3+ years of experience designing, implementing, and scaling production-ready data pipelines for ML training and evaluation is preferred 1+ years of experience serving as a technical lead on ML solutions using industry best practices, patterns, and automation is preferred Prior authorship or co-authorship of a paper on an ML technique, model, or proof of concept is preferred Responsibilities: We work across multiple disciplines, including operations, modeling, and data engineering, and contribute to a range of ML engineering activities We design, build, and deliver ML models and components that address real business challenges in partnership with Product and Data Science teams We use our understanding of ML modeling techniques to guide infrastructure decisions, including model selection, data and feature choices, training, hyperparameter tuning, dimensionality, bias-variance tradeoffs, and validation We solve complex problems by writing and testing application code, developing and validating ML models, and automating testing and deployment We collaborate in cross-functional Agile teams to build and improve software for advanced big data and machine learning applications We retrain, maintain, and monitor models in production We use or create 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 deployment of ML models and application code We ensure code is well managed to reduce vulnerabilities, models are governed from a risk perspective, and ML solutions 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 PyTorch Python Scala Spark TensorFlow numpy pandas Model Training More: We are Capital One, and we are hiring for our Intelligent Foundations and Experiences (IFX) team. This Machine Learning Engineer 4 role is based in New York, NY, with a listed salary range of $215,200 to $245,600 for that location, plus potential performance-based incentive compensation. We offer a comprehensive, competitive, and inclusive benefits package that supports overall well-being, and eligibility varies by employment status and level. Applications are accepted for a minimum of 5 business days. We are an equal opportunity employer and promote a drug-free workplace. We also note that we do not sponsor new employment authorization or provide immigration-related support for this position. last updated 39 week of 2026