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R173946 Posted 08/30/2023

Senior Director - Machine Learning Engineer

Bengaluru, India
  • Category Engineering
  • Experience Sr. Director
  • Primary Address Bangalore, Karnataka

Overview

Voyager (94001), India, Bangalore, Karnataka

Senior Director - Machine Learning Engineer

At Capital One India, we work in an empowering, fast paced and intellectually rigorous environment to solve technical and business problems at scale that are critical to Capital One. Using advanced analytics, AI and machine learning, we derive valuable insights about product and process design, consumer behavior, regulatory and credit risk, and more, from large volumes of data, and use it to build cutting edge patentable products that drive the business forward.

We’re looking for a Senior Director - Machine Learning Engineer to join the Machine Learning Experience (MLX) team!

The MLX team is at the forefront of how Capital One builds and deploys responsible AI/ML models and platforms including more recent Generative AI capabilities such as LLMs and Vector Databases; how we onboard and educate associates on the ML platforms and products that the whole company uses; and how we drive new innovation and research. We're working to seamlessly infuse AI/ML into the fabric of the company. The end to end experience we’re creating will enable our users  to focus their time and resources on advancing their specific machine learning objectives — all while continuing to deliver next-generation machine learning-driven products and services for our customers.  

What you’ll do in the role:

  • Lead an organization made up of machine learning, software, DevOps and data engineers to deliver on an ambitious agenda around building an industry leading machine learning platform that enables the training and serving of thousands of machine learning models.

  • Leverage your experience building large scale systems to lead teams to scale our platform to support thousands of concurrent data scientists, research scientists and MLEs working concurrently to build models that scale.

  • Leverage cloud-based architectures and technologies to deliver optimized enablement of ML models at scale.

  • Optimize data pipelines to feed ML models.

  • Use programming languages like Python, Scala, or Go.

  • Promote best practices in all aspects of the engineering and modeling lifecycles.

  • Recruit, nurture, and retain top engineering talent.

Basic Qualifications

  • Bachelor’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) with overall 15+ years of experience in Engineering

  • At least 6 years of experience programming with Python, Scala, or Go.

  • At least 5 years experience in Machine Learning, Software Engineering, or Data Engineering

  • At least 5 years experience in technology leadership or managing people

  • At least 5 years experience in a cloud environment

Preferred Qualifications

  • Master's or PhD degree in “STEM” field (Science, Technology, Engineering, or Mathematics) with overall 15+ years of experience in Engineering

  • Experience building and supporting a multi-tenant machine learning platform providing model training and/or serving capabilities to users.

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

  • 5+ years experience in any major machine learning frameworks such as XGBoost, PyTorch, Tensorflow or AWS SageMaker

  • 6+ years of experience within a large/data-intensive multi-line business environment.

  • Expertise designing, implementing, and scaling complex production-ready data pipelines for ML models.

  • Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms

  • Ability to communicate complex technical concepts clearly to a variety of audiences.

  • Highly developed interpersonal, presentation, and communications skills.

  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.

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).

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  • Step 3 Interview(s)

    Now’s your chance to learn about the job, show us who you are, share why you would be a great addition to the team and determine if Capital One is the place for you.

  • Step 4 Decision

    The team will discuss — if it’s a good fit for us and you, we’ll make it official!

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A possible career journey at Capital One:

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