Center 1 (19052), United States of America, McLean, Virginia
Distinguished Engineer, Machine Learning
As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud.
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. The Center for Machine Learning is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML.
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 6 years of experience programming in C, C++, Python, or Scala.
- At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.
- At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing
- At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)
Preferred Qualifications
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.
- 8+ years of experience within a large/data-intensive multi-line business environment.
- 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.
- ML industry impact through conference presentations, papers, blog posts, or open source contributions.
- Ability to attract and develop high-performing software engineers with an inspiring leadership style.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer
San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer
Sales Territory: $232,900 - $265,800 for Distinguished Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
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 (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable 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 [email protected] . 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 [email protected]
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).
Top Skills
What We Do
At Capital One, we think and work like a tech company, using our digital fluency to transform everything about the customer experience. We’re bending data to our will, and turning a stodgy industry on its head. That’s reflected in our ranking as the number one business technology innovator in the U.S. in the 2016 InformationWeek Elite 100.
Why Work With Us
Here’s another question: What are you looking for? A place where curiosity is the starting point? Where data leads to human insights? Where humanity drives product development? We’re bringing breakthrough products and services to consumers, small businesses, and commercial clients. And each new idea makes life better for millions of people.
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Employees engage in a combination of remote and on-site work.