Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)

Capital One’s Enterprise Platforms Technology (EPTech) group is seeking a Sr Lead, Machine Learning Engineer to scale ML initiatives from concept to production. In this role, you will design and operationalize machine learning models and the supporting infrastructure, while ensuring governance, security, and robust performance across systems. Based in New York City and focused on enterprise-scale solutions, this onsite position emphasizes collaboration with product and data science teams to solve real business problems through advanced analytics.

Responsibilities

• Design, build, and deliver ML models and components that address real-world business challenges, in partnership with Product and Data Science teams.
• Guide ML infrastructure decisions with a solid understanding of modeling techniques, data, features, training, hyperparameters, dimensionality, bias/variance, and validation.
• Tackle complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Work within a cross-functional Agile team to create and enhance software for state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production environments.
• Utilize cloud-based architectures and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Apply continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure code quality and governance, manage risk related to models, and follow responsible and explainable AI practices.
• Program in Python, Scala, or Java.

Requirements

• Bachelor’s degree
• At least 8 years designing and building data-intensive solutions using distributed computing (internships excluded)
• At least 4 years programming with Python, Scala, or Java
• At least 3 years building, scaling, and optimizing ML systems
• At least 2 years leading teams developing ML solutions

Technologies

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

Benefits

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

Preferred Qualifications

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 4+ years of on-the-job experience with industry recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of developing performant, resilient, and maintainable code
• 3+ years of data gathering and preparation for ML models
• 3+ years of people management experience
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• 3+ years building production-ready data pipelines that feed ML models
• Ability to communicate complex technical concepts clearly to a variety of audiences

Salary and location

Location: New York, NY (onsite)

Salary: USD 250,800 - 286,200 per year

Salary ranges by location

• McLean, VA: $229,900 - $262,400
• New York, NY: $250,800 - $286,200