
location_onFairfax County Fire Station Number 1, McLean, 1455, Laughlin Avenue, Bryn Mawr, McLean, Fairfax County, Virginia, 22101, United States
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 bridge the gap between data science innovation and real-world business impact by building robust, scalable, and responsible AI solutions. We operate at the intersection of Ops, Modeling, and Data Engineering, fostering a culture where continuous learning and the application of the latest industry best practices are central to our daily work.
This role is designed for a technical leader who thrives in a collaborative, cross-functional environment. You will be responsible for the end-to-end lifecycle of machine learning systems, from detailed technical design and development to deployment and monitoring. Your work will directly influence how we solve complex business problems by leveraging state-of-the-art big data and ML technologies.
In this position, you will not only write and test application code but also make critical infrastructure decisions regarding model selection, data pipelines, and feature engineering. You will partner closely with Product and Data Science teams to ensure that our ML models are not only performant but also governed effectively to meet risk and compliance standards, including Responsible and Explainable AI principles. The role offers the opportunity to continuously evolve your skills while delivering optimized ML models that serve millions of customers.
We are committed to a transparent and efficient hiring process. Candidates can expect a structured evaluation designed to assess both technical depth and cultural fit. While specific steps may vary, the process typically involves an initial conversation to discuss your background and interest, followed by technical assessments and team collaboration sessions. We encourage you to review the full job details and apply directly through our careers portal.
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 legal requirements. Our culture is built on inclusivity, and we strive to create an environment where diverse perspectives drive innovation.
Important Notice: At this time, Capital One will not sponsor a new applicant for employment authorization for this position. For candidates requiring an accommodation to apply or participate in the recruiting process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
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
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field. 3+ years of experience building production-ready data pipelines that feed ML models. 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. 2+ years of experience developing performant, resilient, and maintainable code. 2+ years of experience with data gathering and preparation for ML models. 2+ years of people leader experience. 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation. Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform. Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance. ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Skills: Machine Learning, Python, Scala, Java, Distributed Computing, Scikit-Learn, Pytorch, Dask, Spark, Tensorflow.
Education: Bachelor's degree required; Master's in Computer Science preferred; Doctoral degree in Computer Science preferred.