Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible)

Recruiting : VA - McLean, United States of America, McLean, VirginiaSr Distinguished Engineer, Generative AI Systems - (Remote- Eligible)

Sr Distinguished Engineer, Generative AI Systems

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 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.

Capital One is open to hiring a Remote Employee for this opportunity

Basic Qualifications :

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

At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems

At least 6 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.

Capital One will consider sponsoring a new qualified 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) : $321,500 - $366,900 for Sr Distinguished Machine Learning EngineerSan Francisco and San Jose, California (Hybrid On-Site) : $340,500 - $388,700 for Sr Distinguished Machine Learning EngineerRemote (Regardless of Location) : $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer