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Senior Lead Engineer - Generative AI Infrastructure (Remote-Eligible) - San Jose California
Company: Capital One Location: San Jose, California
Posted On: 04/27/2024
NYC 299 Park Avenue (22957), United States of America, New York, New YorkSenior Lead Engineer - Generative AI Infrastructure (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 -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. -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 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:
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