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Senior Distinguished Machine Learning Engineer

Yesterday Bangalore, India

Voyager (94001), India, Bangalore, Karnataka

Senior Distinguished Machine Learning Engineer

As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You'll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.

What you'll do in the role:

  • Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
  • Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
  • Lead large-scale ML initiatives with the customer in mind
  • Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
  • Optimize data pipelines to feed ML models
  • Use programming languages like Python, Scala, C/C++
  • Leverage compute technologies such as Dask and RAPIDS
  • Evangelize best practices in all aspects of the engineering and modeling lifecycles
  • Help recruit, nurture, and retain top engineering talent

Basic Qualifications:

  • Bachelor's degree
  • At least 10 years of experience designing and building data-intensive solutions using distributed computing
  • At least 7 years of experience programming in C, C++, Python, or Scala
  • At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting

Preferred Qualifications:

  • Master's Degree
  • 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models
  • 3+ years of experience using Dask, RAPIDS, or in High Performance Computing
  • 3+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)
  • ML industry impact through conference presentations, papers, blog posts, or open source contributions

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. 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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Client-provided location(s): Bangalore, India
Job ID: capital-R228284
Employment Type: FULL_TIME
Posted: 2025-10-18T19:20:04

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Health Reimbursement Account
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • FSA With Employer Contribution
    • HSA
    • HSA With Employer Contribution
    • On-Site Gym
    • Pet Insurance
    • Mental Health Benefits
    • Virtual Fitness Classes
  • Parental Benefits

    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Adoption Leave
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Commuter Benefits Program
    • Casual Dress
    • Happy Hours
    • Snacks
    • Company Outings
    • On-Site Cafeteria
    • Holiday Events
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Leave of Absence
    • Volunteer Time Off
  • Financial and Retirement

    • 401(K) With Company Matching
    • Stock Purchase Program
    • Performance Bonus
    • Relocation Assistance
    • Financial Counseling
    • Profit Sharing
  • Professional Development

    • Tuition Reimbursement
    • Promote From Within
    • Mentor Program
    • Shadowing Opportunities
    • Access to Online Courses
    • Lunch and Learns
    • Internship Program
    • Work Visa Sponsorship
    • Leadership Training Program
    • Associate or Rotational Training Program
  • Diversity and Inclusion

    • Diversity, Equity, and Inclusion Program
    • Employee Resource Groups (ERG)
    • Founder led

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