Distinguished Engineer - Card Machine LearningAt 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. Card Tech Machine Learning (CTML) 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 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.
You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions.
At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence, and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring internal talent and actively recruiting to keep building our community.
Distinguished Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization.
In this role you will work at the intersection of Machine Learning and Data Engineering. Specifically, we have an ambitious goal to reduce time to market of our business critical models by 50% which will require platform thinking and pipeline optimization/automation with a goal of making model deployment pipelines self-serve as much as possible and 'templatizing' approaches. You will be required to influence across Data Science, MLEs, Tech and Product organizations to create a destination target state for the organization that achieves our goals, creating a multi-year blueprint on how Data, ML and MLOps can effectively interwork for success. You will also be at the forefront of GenAI initiatives working with multiple Card Tech partners and Enterprise groups to envision, develop PoCs and help take GenAI ideas to market for Card in partnership with Enterprise.
If you are ready to provide thought leadership and build engineering excellence across Capital One's engineering teams, come join us in our mission to change banking for good.
Key responsibilities: Articulate and evangelize a bold technical vision for your domain.Decompose complex problems into practical and operational solutions.Ensure the quality of technical design and implementation.Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability.Continue learning and injecting advanced technical knowledge into our community.Handle several projects simultaneously, balancing your time to maximize impact.Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community.Effective storyteller that can tie business objectives and tech imperatives in a cohesive manner.Deliver ML models to production 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.Basic QualificationsBachelor's Degree.At least 7 years of experience in software engineering and solution architecture.At least 7 years of experience in enterprise architecture and design patterns.At least 5 years of experience in data engineering using Spark, Python, Java, or Scala.At least 3 years of experience in cloud computing (AWS, Microsoft Azure, Google Cloud).At least 2 years of experience in the MLOps development lifecycle using AI and ML frameworks.Preferred Qualifications:Bachelor's or Master's Degree in Computer Science or a related field.10+ years of professional experience coding in Java, Python, or Scala.10+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support.3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.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 Engineer.
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.
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.
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