Distinguished Engineer - Machine Learning Engineer - Consumer Engagement Platform (Remote Eligible)

Distinguished Engineer - Machine Learning Engineer - Consumer Engagement Platform (Remote Eligible)

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.

The Customer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all of Capital One’s consumer products and organizations by providing well-managed, self-service, experimentation-driven, and personalized product development. We are seeking a Distinguished Engineer to define, architect, and drive the implementation of our Personalization Platform. We are building a scalable infrastructure powering real-time, hyper-personalized experiences, from personalized home feeds to targeted messaging for millions of users across all of Capital One’s Financial products. 

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

What you’ll do: 

• Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services

• Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users

• Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations.

• Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability.

• Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals.

• Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems