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Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Date Posted: Jul 07, 2026
Yearly: USD - USD

Job Detail

  • location_on
    Location Virginia, United States of America
  • desktop_windows
    Job Type: Permanent
  • schedule
    Shift:
  • analytics
    Career Level:
  • group
    Positions:
  • calendar_view_day
    Experience:
  • male
    Gender: No Preference
  • school
    Degree:
  • calendar_month
    Apply Before: Oct 05, 2026

Job Description

Overview

Sr. Distinguished Machine Learning Engineer (Remote-Eligible) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One's consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale - turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org's mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment. What you'll do in the role: 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, guardrails, model evaluation, 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, and scalable monitoring & observability. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation. The Ideal Candidate: You love to build systems

Key responsibilities

Not specified in the original listing.

Required skills

  • I.T. & Communications

What the company offers

Not specified in the original listing.

Skills Required

Company Overview

Harrisonburg, Virginia, United States of America

Capital One is a financial services company focused on technology and innovation in banking. They leverage machine learning to enhance customer experiences and deliver personalized banking services. The company is dedicated to responsible AI developm... Read More

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