Capital One Distinguished Engineer Generative AI Systems Eligible 

United States, California, San Francisco 

858743378

We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that’s designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include:

• 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 infrastructure for serving large ML models, in our public cloud.

• 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 implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection

• Develop applications that leverage LLMs and FMs.

• Design and implement capabilities to support MLOps for foundation models.

Basic Qualifications:

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

• At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems

• At least 5 years of experience developing AI and ML algorithms in Python or C/C++

• At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud.

Preferred Qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques.

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

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

• Experience with delivering very large models through the MLOps life cycle from exploration to serving.

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

• Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc.

• Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning.

• Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML.

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.