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

The Senior Lead, Machine Learning Engineer role within Capital One's Enterprise Platforms Technology (EPTech) team in New York, NY (onsite) focuses on productionizing ML applications at scale, designing and implementing models and infrastructure, and ensuring governance, security, and performance of ML systems.

Responsibilities

• Design and deliver ML models and components that address real-world business needs, in collaboration with Product and Data Science teams.
• Guide ML infrastructure decisions based on modeling techniques and considerations, including model choice, data and feature selection, 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.
• Collaborate within a cross-functional Agile team to build software that enables 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 quality and governance to reduce vulnerabilities, maintain risk governance for models, and adhere to responsible and explainable AI practices.
• Utilize 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
• 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 an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with 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 of experience building production-ready data pipelines that feed ML models
• Ability to communicate complex technical concepts clearly to a variety of audiences

Salary by Location

• McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer
• New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer