Senior Manager, Machine Learning Engineering
Not Disclosed•Full-TimeOn-site
location_onFairfax County Fire Station Number 1, McLean, 1455, Laughlin Avenue, Bryn Mawr, McLean, Fairfax County, Virginia, 22101, United States
About the Team
As a Capital One Machine Learning Engineer (MLE), you will join an Agile team dedicated to productionizing machine learning applications and systems at scale. Our mission is to leverage existing and emerging technology platforms to drive innovation, ensuring high availability and performance for our machine learning applications. We foster a culture of continuous learning, encouraging engineers to apply the latest innovations and best practices in machine learning engineering to solve real-world business problems.
About the Role
This Senior Manager position sits at the intersection of Operations, Modeling, and Data Engineering. You will lead cross-functional teams to design, build, and deliver ML models that enhance state-of-the-art big data and ML applications. Beyond technical architecture, you will be responsible for the full lifecycle of ML systems, from retraining and monitoring models in production to constructing optimized data pipelines. A key focus of this role is ensuring responsible and explainable AI, maintaining well-governed models, and reducing vulnerabilities through rigorous code management and deployment best practices.
Hiring Process
Capital One is committed to a fair and efficient hiring process. We expect applications to be accepted for a minimum of 5 business days. Please note that no agencies are accepted for this position. If you require an accommodation during the recruiting process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential.
Equal Opportunity & Culture
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. We promote a drug-free workplace and consider qualified applicants with a criminal history in a manner consistent with relevant laws. We strive to create an inclusive environment where diverse backgrounds are valued.
Work location
Work model: On-site
Fairfax County Fire Station Number 1, McLean, 1455, Laughlin Avenue, Bryn Mawr, McLean, Fairfax County, Virginia, 22101, United States
McLean, Virginia
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Skills, education and keywords
Skills: Machine Learning, Python, Scala, Java, Scikit-Learn, Pytorch, Dask, Spark, Tensorflow, Aws.
Education: Bachelor's Degree required; Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or similar field preferred.
Frequently asked questions about Senior Manager, Machine Learning Engineering at Capital One
What does a Senior Manager, Machine Learning Engineering at Capital One do?expand_more
In this Senior Manager, Machine Learning Engineering at Capital One role, you will design, build, and deliver ml models and components to solve real-world business problems; develop and review model and application code using python, scala, or java; construct optimized data pipelines to feed ml models; and leverage cloud-based architectures to deliver optimized ml models at scale.
What are the requirements for this Senior Manager, Machine Learning Engineering role?expand_more
To qualify for the Senior Manager, Machine Learning Engineering at Capital One position, applicants should have: Bachelor's Degree; 8+ years designing data-intensive solutions using distributed computing; 4+ years programming with Python, Scala, or Java; 3+ years building, scaling, and optimizing ML systems; 2+ years leading teams developing ML solutions; and 4+ years people management experience.
Where is the Senior Manager, Machine Learning Engineering role at Capital One located?expand_more
Senior Manager, Machine Learning Engineering at Capital One is based in Fairfax County Fire Station Number 1, McLean, 1455, Laughlin Avenue, Bryn Mawr, McLean, Fairfax County, Virginia, 22101, United States. This is a on-site role.