#hiring *Distinguished Engineer, Generative AI Systems (Remote Eligible)*, San Francisco, *United States*, $314K, fulltime #opentowork #jobs #jobseekers #careers $314K #SanFranciscojobs #Californiajobs #ITCommunications
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Locations: Sales - CA - San Francisco, United States of America, San Francisco, CaliforniaDistinguished Engineer, Generative AI Systems (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 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 Qua
