Hybrid Senior Lead, Machine Learning Engineer – Enterprise Platform Technology

at Capital One

• Job title: Senior Lead, Machine Learning Engineer – Enterprise Platform Technology
• Job type: Full Time
• Experience level: Senior
• Salary: $225,400 - $280,600 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Google Cloud Platform, Java, Open Source, Python, PyTorch, Scala, Scikit-Learn, Spark, Tensorflow
• Location requirements: Hybrid, New York City, United States

About the role

• Senior Lead Machine Learning Engineer at Capital One responsible for designing and implementing scalable machine learning applications. Collaborating in an Agile team to optimize and maintain production-ready models.

Responsibilities

• Part of an Agile team dedicated to productionizing machine learning applications and systems at scale
• Participate in the detailed technical design, development, and implementation of machine learning applications
• Focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Collaborate as part of a cross-functional Agile team to create and enhance software
• Retrain, maintain, and monitor models in production
• Leverage or build cloud-based architectures to deliver optimized ML models
• Construct optimized data pipelines to feed ML models
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed, and follow best practices in AI

Requirements

• Bachelor’s degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing
• 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
• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field (preferred)
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred)
• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
• 3+ years of experience developing performant, resilient, and maintainable code (preferred)
• 3+ years of experience with data gathering and preparation for ML models (preferred)
• 3+ years of people management experience (preferred)
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents (preferred)
• 3+ years of experience building production-ready data pipelines that feed ML models (preferred)
• Ability to communicate complex technical concepts clearly to a variety of audiences (preferred).

Benefits

• Comprehensive and competitive health benefits
• Financial and other benefits that support total well-being