Center 2 (19050), United States of America, McLean, Virginia

Distinguished Engineer - Machine Learning Architecture (Remote- Eligible)

Distinguished Engineer - Machine Learning Architecture

Capital One is committed to becoming a leader in machine learning, using it to deliver world-class financial services products and experiences to our customers. We are seeking a Distinguished Engineer to work on our machine learning platform and help lead, build and drive this transformation across our entire company. This individual will be part of our technology organization, and will lead through technical subject matter expertise, 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 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. 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. We have recruited the best technology talent in financial services. We are increasingly becoming a platform-oriented company with data, feature and machine learning platforms as key drivers for our business.

At Capital One we believe that machine learning represents the biggest opportunity in financial services today, and is a chance to revolutionize the industry. Capital One's commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company.

Our Distinguished Engineers 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.
  
• Visionaries, collaborating on and solving Capital One's toughest issues, to deliver on business needs that directly impact the lives of millions of our customers and associates.
  
• Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community.
  
• Developer Advocates, both internally and externally, elevating the Engineering Community and a go-to resource on technologies and capabilities.
  
• Leaders who gain the trust and confidence of those around them, from hands-on engineers to executives.
  

Responsibilities:

• Grow a world-class machine learning architectural practice by helping to build and lead a team of the brightest technical minds.
  
• Oversee a platform level architectural workstream by collaborating across delivery teams and towers to identify and solve the most impactful technical problems.
  
• Build a vision and roadmap, defining what the priorities should be, and creating both near-term and long-term wins from the application of machine learning.
  
• As a naturally curious leader, continually assess the landscape of new machine learning frameworks, tools, and platforms for new capabilities that will drive the next generation of our platform.
  
• Create a robust operating model for machine learning development lifecycle to provide an efficient and well managed path from exploratory data analysis to prototype to full enterprise-class capabilities for our customers.
  
• Nurture a healthy collaborative engineering culture, and communicate clear tradeoffs to business and technology leaders that align business objectives with technology implementation.
  
• Partner with our enterprise risk partners to stand up proper governance and oversight of machine learning capabilities.
  

Capital One is open to hiring a Remote Employee for this opportunity.

Basic Qualifications:

• Bachelor's Degree
  
• At least 7 years of experience in software development or software engineering
  

Preferred Qualifications:

• Masters or PhD in Machine Learning or Artificial Intelligence
  
• 12+ years of experience architecting and developing software systems or platforms
  
• 4+ years of experience with platforms supporting the Machine Learning development lifecycle
  
• 4+ years of experience with data pipelines and distributed compute with Spark or Dask
  
• 4+ years of experience with Kubernetes or Docker
  
• 3+ years of experience with hands on programming (Java, Scala, Go, Python)
  
• 3+ years of experience developing machine learning models
  
• 3+ years of experience in AWS
  

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

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).