Senior Machine Learning Engineer (AI Foundations)

Benefits at Capital One include health benefits, financial benefits, and performance-based incentive compensation. This onsite Senior Machine Learning Engineer role in McLean, VA offers the opportunity to work on productionizing ML applications at scale, with exposure to the latest ML engineering practices. Salary ranges from USD 161,800 to 184,600 per year.

Senior Machine Learning Engineer (AI Foundations) is part of an Agile team focused on productionizing ML applications at scale. The role emphasizes ML architectural design, developing and reviewing model and application code, and ensuring high availability and performance of ML systems.

Responsibilities

• Design, build, and deliver ML models and components that address real-world business needs, partnering with Product and Data Science teams.
• Inform ML infrastructure decisions by applying knowledge of modeling techniques, data, feature selection, model training, hyperparameters, dimensionality, bias/variance, and validation.
• Tackle complex challenges by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate within a cross-functional Agile team to create software enabling state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure code is well-managed to reduce vulnerabilities, with models governed from a risk perspective and aligned with Responsible and Explainable AI principles.
• Use programming languages such as Python, Scala, or Java.

Requirements

• Bachelor’s Degree
• At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)
• At least 3 years of experience designing and building data-intensive solutions using distributed computing
• At least 2 years of on-the-job experience with an industry-recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
• At least 1 year of experience productionizing, monitoring, and maintaining models

Technologies

• Python
• Scala
• Java
• scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow