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Sr. Director, Machine Learning Engineering (Remote-Eligible)

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OREGON EMPLOYMENT DEPARTMENT

Salem, MA (In Person)

Part-Time

Posted 4 weeks ago (Updated 1 week ago) • Actively hiring

Expires 6/7/2026

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Job Description

Job Listing ID:
4469877
Job Title:
Sr. Director, Machine Learning Engineering (Remote-Eligible)
Application Deadline:
Open Until Filled
Job Location:
Salem
Date Posted:
04/10/2026
Hours Worked Per Week:
Not Provided Shift:
Not Provided Duration of Job:
Either Full or Part Time, more than 6 months You may contact this employer directly. (Obtain the contact information to print or add to your jobs.)
Job Summary:
Sr. Director, Machine Learning Engineering (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: Lead and scale a high-performing engineering organization responsible for the Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across Capital One products and services. Define the technical strategy, delivery roadmap, and operating model for a portfolio spanning recommendation systems, ranking, decisioning, GenAI infrastructure, MLOps, and low-latency application-serving systems Build, develop, and manage engineers and engineering leaders; set a high bar for hiring, performance, talent density, coaching, and succession planning across the organization Partner cross-functionally with Product, Data Science, Cloud Infrastructure, and Machine Learning Platform teams to align strategy, prioritize investments, and co-develop advanced recommendation systems and algorithms serving Capital One users Drive the design, buildout, and operation of robust ML infrastructure and pipelines supporting feature extraction, model training, testing, guardrails, evaluation, deployment, and both real-time and batch inference with strong reliability, scalability, and operational rigor Architect low-latency, event-driven systems for real-time personalization and decisioning based on streaming data, user behavior, and contextual signals Drive the evolution of MLOps practices through automated, metrics-backed deployment workflows, validation and testing systems, model lifecycle governance, and scalable observability Guide the adoption of state-of-the-art AI and LLM optimization techniques to improve scalability, cost, latency, throughput, and reliability of large-scale production AI systems Provide organizational ...
Job Classification:
Computer Occupations, All Other Access our statewide or regional occupation report for more information about wages, employment outlooks, skills, training programs, related occupations, and more. Compensation
Salary:
Not Provided Job Requirements
Experience Required:
 See Job Summary
Education Required:
None
Minimum Age:
N/A Gender:
N/A

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