Machine Learning Engineer (AI Foundations)

Capital One is expanding its AI foundations team to scale machine learning applications across the business. The Machine Learning Engineer (AI Foundations) will partner with product and data science teams to design, deploy, monitor, and govern ML solutions in production, incorporating responsible AI practices along the way. This role focuses on productionizing models at scale and delivering measurable business impact through collaborative engineering and robust ML infrastructure.

The position invites hands-on work across model development, deployment, monitoring, and continuous improvement in a cloud-enabled environment, all while maintaining governance and explainability standards.

Role details

• Location: McLean, VA (onsite)
• Salary: USD 135,600 to 154,800 per year
• Education: Bachelor’s Degree
• Minimum experience: 1 year

Responsibilities

• Develop and deploy machine learning models and supporting components that address tangible business needs, partnering with Product and Data Science squads.
• Guide ML infrastructure choices by applying modeling concepts such as data selection, feature engineering, training, hyperparameter tuning, bias and variance considerations, and validation strategies.
• Tackle complex problems through building and validating code, creating ML solutions, and automating testing and deployment processes.
• Work within an Agile, cross functional team to build software that powers advanced big data and ML applications.
• Periodically retrain, maintain, and monitor models in production environments.
• Apply or construct cloud based architectures and platforms to deploy scalable, optimized ML models.
• Design efficient data pipelines that feed ML models with the right data at the right time.
• Implement CI/CD practices including test automation and monitoring to ensure reliable deployment of models and code.
• Keep codebases secure, ensure governance of models from risk perspective, and adhere to Responsible and Explainable AI practices.
• Proficiency in Python, Scala, or Java.

Requirements

• Educational background: Bachelor’s Degree.
• Minimum of two years designing and delivering data-driven solutions on distributed computing platforms. Internship experience does not apply.
• At least two years programming in Python, Scala, or Java.
• Minimum one year applying machine learning with a recognized framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.

Technologies

• Python
• Scala
• Java
• scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow
• AWS
• Azure
• Google Cloud Platform

Benefits

• Health, financial and other benefits that support your total well-being
• Performance-based incentive compensation, which may include cash bonuses and/or long term incentives (LTI)