Director Software Engineering - Center for Machine Learning

Capital One is committed to becoming a leader in machine learning, and using machine learning to deliver better financial services to our customers. We are seeking a Director of Software Engineering to help lead, build and drive the continued growth of our machine learning model training platform. This individual will be part of our technology organization, and will lead teams building machine learning platforms and tools that transform the way we make decisions.

Capital One’s technology organization leads the financial services industry. We have adopted the public cloud (AWS) for our technology infrastructure, and this provides the compute and storage capabilities necessary to power machine learning at a scale and speed that was not previously possible using on-prem offerings. We are undertaking a massive transformation in our data ecosystem to enable real-time streaming data and modern analytics platforms that can handle the volume and variety of data available at Capital One.

At Capital One we believe that machine learning represents the biggest opportunity in financial services today. Our goal is to revolutionize the industry through real-time intelligent platforms. Capital One’s commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company.

Our Directors Are:

• Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices

• Strong people leaders who are experienced in leading engineers and managers of engineers.

• Visionaries, helping solve Capital One’s toughest technology challenges, to deliver on business needs that directly impact the lives of millions of our customers and associates

• Experts in recruiting and managing technical teams, including performance management

• Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community

Responsibilities:

• Build a world-class machine learning platform at Capital One by tackling some seriously thorny issues like infrastructure complexity abstraction, data access and feature registration, integration with back-end Capital one systems, how to scale a massive model training offering while remaining efficient and well managed, how to do all of this while maintaining a slick and easy to use user experience.

• Set vision to truly disrupt the financial services industry through leading edge machine learning capabilities. Build the vision and the roadmap as to where the organization will go, what the priorities should be, creating both near-term and long-term wins from the delivery of the foundational platform that all machine learning will run on.

• As a naturally curious leader, stay abreast of and determine how to fully leverage existing and emerging machine learning offerings where applicable.

• Contribute to developing a robust operating model for machine learning applications that provides a clear development path from POC to prototype to full enterprise-class capabilities.

• Nurture a healthy collaborative engineering culture, and provide transparency to business and technology leaders on selection and prioritization of machine learning capabilities and their progress.

• Partner with the enterprise risk partners to stand up proper governance and oversight of machine learning capabilities.

Basic Qualifications:

• Bachelor’s Degree

• At least 7 years of experience in Software Engineering

• At least 5 years of people management experience

• At least 4 years of working with a data or Machine Learning platform.

• At least 4 years of experience in cloud native development

Preferred Qualifications:

• Masters Degree

• 8 years of experience in building a multi-tenant platform and scaling.

• 6 years of experience in AWS

• 4 years experience working with Machine Learning platforms (SageMaker, EMR, KubeFlow, Vertex AI)

• 5 years of experience with machine learning, deep learning, and statistical modeling using Scikit Learn, XGBoost, TensorFlow, Keras, or PyTorch.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.