Capital One Senior Lead Engineer - Generative AI Infrastructure Remote-Eligible 

United States, New York, New York 

560078470

NYC 299 Park Avenue (22957), United States of America, New York, New York Senior Lead Engineer - Generative AI Infrastructure (Remote-Eligible)

We are looking for an experienced Sr. Lead Engineer, Generative AI Infrastructure to help us build the foundations of our AI capabilities. You will work on a wide range of initiatives, whether that’s building large-scale distributed training clusters, or deploying LLMs on GPU instances for real-time applications and decisioning systems, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work closely with our cloud and container infrastructure teams as well as our world-class team of AI researchers to design and implement key capabilities. Examples of projects you will work on:

• Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud.

• Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries.

• Design and build run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud.

• Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our capabilities.

Basic Qualifications:

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

• At least 8 years of experience designing and building data-intensive solutions using distributed computing

• At least 8 years of experience programming with Python, Go, Scala, or Java

• At least 1 year of experience with HPCs, vector embedding, or semantic search technologies

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

Preferred Qualifications:

• Master's or Doctoral degree in Computer science, Computer Engineering, Electrical engineering, Mathematics, or a similar field.

• Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures.

• Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML etc.

• 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.

• Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking.

This 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.