
location_on2144, Cliffside Drive, Plano, Collin County, Texas, 75023, 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.
This position serves as a critical intersection of Operations, Modeling, and Data Engineering. You will be responsible for the end-to-end lifecycle of machine learning applications, from detailed technical design and development to deployment and monitoring. Your work will directly influence how we solve complex business problems using state-of-the-art big data and ML technologies.
In this role, you will collaborate closely with Product and Data Science teams to design, build, and deliver ML models that drive tangible results. You will leverage your understanding of ML modeling techniques to make informed infrastructure decisions regarding model selection, data pipelines, and feature engineering. A key part of your day involves ensuring high availability and performance of our applications while adhering to best practices in Responsible and Explainable AI.
You will have the opportunity to continuously learn and apply the latest innovations in machine learning engineering, working with cloud-based architectures to optimize models at scale. Your contributions will help create and enhance software that enables the next generation of data-intensive solutions.
Candidates are expected to submit applications for a minimum of 5 business days. The recruitment process includes a review of qualifications followed by interviews. Please note that no agencies are accepted for this position.
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 for employment qualified applicants with a criminal history in a manner consistent with legal requirements.
We offer a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being. If you require 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. All information provided will be kept confidential.
Immigration Note: At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position.
On-site
Skills: Machine Learning, Python, Scala, Java, Distributed Computing, Scikit-Learn, Pytorch, Dask, Spark, Tensorflow.
Education: Bachelor's degree required; Master's or doctoral degree in computer science, electrical engineering, mathematics, or similar field preferred.
2144, Cliffside Drive, Plano, Collin County, Texas, 75023, United States
Plano, Texas
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.
Recrutus helps candidates discover roles that match their skills and helps teams reach qualified applicants faster. Browse by metro, discipline, or work style — from internships to senior leadership.