Senior Lead Machine Learning Engineer

Capital One is seeking an onsite Senior Lead Machine Learning Engineer in New York, NY to scale production-ready ML applications. In this role, you will lead the end-to-end lifecycle of ML design, development, deployment, and governance within an Agile team, partnering with product managers and data scientists to translate data into impactful software. The position emphasizes building robust models and scalable architectures that support data-driven decision making.

Responsibilities

• Develop and deliver machine learning models and components that address real-world business problems, in collaboration with product and data science teams.
• Guide ML infrastructure decisions based on modeling techniques and issues, including model choice, data selection, feature engineering, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
• Tackle complex problems by writing and validating application code, building ML models, and automating tests and deployment pipelines.
• Collaborate within a cross-functional Agile team to create and enhance software that enables advanced big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Utilize or build cloud-based architectures and platforms to deliver optimized ML models at scale.
• Design 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 is well-managed to reduce vulnerabilities and that models are governed from a risk perspective, following 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 apply)
• 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
• AWS
• Azure
• Google Cloud Platform
• scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow

Benefits

• Performance-based incentive compensation (cash bonuses and/or long-term incentives)
• Health benefits
• Financial benefits