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, Python, PyTorch, Scala, Scikit-Learn, Spark, Tensorflow
• Location requirements: Hybrid, New York City, United States

About the role

• Senior Lead Machine Learning Engineer involved in the technical design, development, and implementation of ML applications. Part of an Agile team at Capital One optimizing and scaling ML solutions.

Responsibilities

• Participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
• Focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
• Perform ML engineering activities, including design, build, and/or deliver ML models and components that solve real-world business problems.
• Inform ML infrastructure decisions using knowledge of ML modeling techniques and issues.
• 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 that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, and that models are well-governed from a risk perspective.

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)
• 3+ years of experience building production-ready data pipelines that feed ML models (preferred)

Benefits

• Health insurance
• Performance based incentive compensation
• Cash bonus(es)
• Long term incentives (LTI)
• Comprehensive and competitive benefits