Lead Machine Learning Engineer (MLOps, KServe building Kubernetes Clusters, PyTorch, TensorFlow on AWS)
Not Disclosed•Full-TimeOn-site
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
About the Team
The Intelligent Foundations and Experiences (IFX) team sits at the center of Capital One's vision for AI. We work hand-in-hand with partners across the company to advance the state of the art in science and AI engineering. Our mission is to build and deploy proprietary solutions that are central to our business, delivering value to millions of customers. By empowering teams across Capital One to enhance their products with the transformative power of AI, we aim to create responsible and scalable solutions with the highest leverage impact.
About the Role
As a Lead Machine Learning Engineer, you will join an Agile team dedicated to productionizing machine learning applications and systems at scale. This role is a unique intersection of Operations, Modeling, and Data Engineering. You will participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
In this position, you will focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our ML applications. You will collaborate with Product and Data Science teams to solve complex problems, writing and testing application code, automating tests, and managing the deployment of models. You will also be responsible for retraining, maintaining, and monitoring models in production, ensuring they are well-governed from a risk perspective and adhere to best practices in Responsible and Explainable AI.
Hiring Process
Candidates are expected to go through a standard interview process which typically includes an initial screening, technical deep-dives, and team fit assessments. For specific details on the current stage of the hiring cycle, please refer to the application portal.
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 for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws.
Capital One values diversity and inclusion, fostering a culture where everyone can bring their authentic selves to work. We are committed to providing reasonable accommodations for individuals with disabilities or religious beliefs during the recruiting process. If you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
Note on Immigration: At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position.
Similar Job Opportunities
Skills, education and keywords
Skills: Machine Learning, Mlops, Kserve, Kubernetes, Pytorch, Tensorflow, Aws, Python, Scala, Java.
Education: Bachelor's degree required; Master's or doctoral degree in computer science, electrical engineering, mathematics, or similar field preferred.
Frequently asked questions about Lead Machine Learning Engineer (MLOps, KServe building Kubernetes Clusters, PyTorch, TensorFlow on AWS) at Capital One
What does a Lead Machine Learning Engineer (MLOps, KServe building Kubernetes Clusters, PyTorch, TensorFlow on AWS) at Capital One do?expand_more
Day-to-day, the Lead Machine Learning Engineer (MLOps, KServe building Kubernetes Clusters, PyTorch, TensorFlow on AWS) at Capital One 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 Lead Machine Learning Engineer (MLOps, KServe building Kubernetes Clusters, PyTorch, TensorFlow on AWS) role?expand_more
To qualify for the Lead Machine Learning Engineer (MLOps, KServe building Kubernetes Clusters, PyTorch, TensorFlow on AWS) at Capital One position, applicants should have: Bachelor's degree; 6+ years designing data-intensive solutions using distributed computing; 4+ years programming with Python, Scala, or Java; 2+ years building, scaling, and optimizing ML systems; Master's or doctoral degree in computer science, electrical engineering, mathematics, or similar field (preferred); and 3+ years building production-ready data pipelines for ML models (preferred).