Capital One Senior Engineer - Generative AI Product Engineering Remote-Eligible 

United States, Virginia, Arlington 

796777496

Center 2 (19050), United States of America, McLean, Virginia Senior Engineer - Generative AI Product Engineering (Remote-Eligible)

We are looking for an experienced Senior Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include:

• Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs.

• Design APIs for performance, real-time applications, scale, ease of use and governance automation.

• Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience.

• Enable our users to build new GenAI capabilities.

• Develop tools and processes to monitor API access patterns and operational health.

• Design and implement AI safety and guardrails in the API layer working closely with researchers

Basic Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering or a technical field

• At least 4 years of experience designing and building and deploying ML application platforms.

• At least 4 years of experience programming with Python, Go, Scala, or Java

• At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks

Preferred Qualifications:

• Familiarity with building large-scale AI and ML products or platforms serving millions of users.

• Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.

• Experience with Kubernetes and KubeFlow workloads is preferred.

• Familiarity with the Model Development Lifecycle and MLOps preferred.

• Experience architecting cloud systems for security, availability, performance, scalability, and cost.

• Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines.

• Experience at tech and product-driven companies/startups preferred.

• Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities.

• Have experience with API security, observability, cloud access control and privacy best practices.

New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning Engineer San Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning EngineerThis role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.