Machine Learning Engineer

Salary: $197,300 - 225,100 per year Requirements: Bachelors degree or higher in Computer Science, Machine Learning, or another quantitative discipline such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering At least 4 years of programming experience with Python, Java, Golang, or C++ At least 4 years of machine learning experience using PyTorch or TensorFlow and related libraries such as Pandas, NumPy, and Scikit-learn At least 4 years of experience working with large-scale distributed systems such as Spark or Ray to prepare AI/ML data At least 2 years of experience deploying and running machine learning solutions in production and operating cloud-based production services in AWS, GCP, or Azure At least 2 years of experience using Kubernetes to manage large-scale containerized ML software systems Preferred: masters or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field Preferred: 3+ years of experience optimizing ML algorithms, configurations, and infrastructure Preferred: 3+ years of experience applying software development best practices, including source control, testing, code reviews, and CI/CD Preferred: 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment methods, monitoring, alerts, and incident response planning Preferred: 3+ years of experience with machine learning approaches such as supervised, semi-supervised, unsupervised, and reinforcement learning, as well as models including regression, classification, and clustering Preferred: 3+ years of experience with ML architectures such as RNNs, CNNs, LSTMs, and Transformers, plus training concepts like loss functions, hyperparameters, and regularization Preferred: 3+ years of experience designing, implementing, and scaling production-ready data pipelines for ML training and evaluation Preferred: 1+ years of experience serving as a technical lead on ML solutions using industry best practices, patterns, and automation Preferred: authorship or co-authorship of a paper on an ML technique, model, or proof of concept Responsibilities: Work across Ops, Modeling, and Data Engineering to support machine learning engineering activities Design, build, and deliver ML models and components that address real business problems in partnership with Product and Data Science teams Use knowledge of model choice, data selection, feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation to guide ML infrastructure decisions Write and test application code, develop and validate ML models, and automate testing and deployment to solve complex problems Collaborate on cross-functional Agile teams to create and improve software for advanced big data and ML applications Retrain, maintain, and monitor models in production Build or use cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale Create efficient data pipelines to feed ML models Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful model and application delivery Ensure code is well-managed to reduce vulnerabilities, models are governed appropriately from a risk perspective, and ML work follows Responsible and Explainable AI best practices 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 looking for Machine Learning Engineers who are excited to build in the AI and technology space and help solve complex business problems in a fast-paced, collaborative, inclusive, and iterative environment. You will join a large team of makers, breakers, doers, and disruptors focused on real customer needs and major AI transformation work across our organization. This role is based in McLean, VA, with a stated salary range of $197,300 to $225,100 for that location, and it may also be eligible for performance-based incentive compensation. We offer a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well-being, with eligibility varying by employment status and level. last updated 39 week of 2026