Senior Lead Machine Learning Engineer

Capital One is seeking a Senior Lead Machine Learning Engineer to drive the productionization of ML applications at scale within an Agile team. The role centers on shaping ML architecture, reviewing model and application code, and ensuring the high availability and performance of ML systems in production.

Location: McLean, VA (onsite)

Salary: USD 229,900 - 262,400 per year

Responsibilities

• Design, build, and deliver ML models and components that address real business needs, collaborating with Product and Data Science teams.
• Inform ML infrastructure decisions with a solid understanding of modeling techniques, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
• Develop and test application code, train and validate ML models, and automate tests and deployment.
• Collaborate within a cross-functional Agile team to create and enhance software enabling state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production environments.
• 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 reliable deployment of ML models and application code.
• Ensure code quality and governance to reduce vulnerabilities, uphold risk standards, and follow Responsible and Explainable AI practices.
• Work with programming languages such as Python, Scala, or Java.

Requirements

• Bachelor's Degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing; internship experience does not count toward this requirement.
• At least 4 years of experience programming with Python, Scala, or Java
• At least 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions

Technologies

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

Benefits

• Performance-based incentive compensation
• Health benefits
• Financial benefits