Lead Engineer - Generative AI Product Engineering (Remote Eligible)

Center 3 (19075), United States of America, McLean, VirginiaLead Engineer - Generative AI Product Engineering (Remote Eligible)

Lead Engineer - Generative AI Product Engineering(Remote Eligible)

Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good.

For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences.

From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking.

Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI.

We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.

At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

We are looking for an experienced Lead 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 6 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques

At least 6 years of experience programming with Python, Go, Scala, or Java

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

Preferred Qualifications :

Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users.

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.

Familiarity with deploying large neural network models in demanding production environments.

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

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York City (Hybrid On-Site) : $201,400 - $229,900 for Lead Machine Learning EngineerSan Francisco, California (Hybrid On-Site) : $213,400 - $243,500 for Lead Machine Learning EngineerRemote (Regardless of Location) : $170,700 - $194,800 for Lead Machine Learning Engineer