Blackwomenintech
Lead Engineer Generative AI Product Engineer
Blackwomenintech, San Francisco, California, United States, 94199
Center 3 (19075), United States of America, McLean, VirginiaLead Engineer - Generative AI Product Engineering
(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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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 Lead Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include:Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs.Design APIs for performance, real-time applications, scale, ease of use and governance automation.Develop application-specific interfaces that leverage LLMs and FMs to enhance the associate and customer experience.Enable our users to build new GenAI capabilities.Develop tools and processes to monitor API access patterns and operational health.Design and implement AI safety and guardrails in the API layer working closely with researchers.Basic Qualifications:
Bachelor's degree in Computer Science, Computer Engineering or a technical field.At least 6 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques.At least 6 years of experience programming with Python, Go, Scala, or Java.At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks.Preferred Qualifications:
Familiarity with building large-scale AI and ML products or platforms serving millions of users.Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.Experience with Kubernetes and KubeFlow workloads.Familiarity with the Model Development Lifecycle and MLOps.Experience architecting cloud systems for security, availability, performance, scalability, and cost.Ability to move fast in an environment with ambiguity and competing priorities.Experience at tech and product-driven companies/startups.Ability to iterate rapidly with researchers and engineers to improve product experience while building foundational capabilities.Experience with API security, observability, cloud access control and privacy best practices.Familiarity with deploying AI or ML models in demanding production environments.This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace.
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(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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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 Lead Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include:Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs.Design APIs for performance, real-time applications, scale, ease of use and governance automation.Develop application-specific interfaces that leverage LLMs and FMs to enhance the associate and customer experience.Enable our users to build new GenAI capabilities.Develop tools and processes to monitor API access patterns and operational health.Design and implement AI safety and guardrails in the API layer working closely with researchers.Basic Qualifications:
Bachelor's degree in Computer Science, Computer Engineering or a technical field.At least 6 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques.At least 6 years of experience programming with Python, Go, Scala, or Java.At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks.Preferred Qualifications:
Familiarity with building large-scale AI and ML products or platforms serving millions of users.Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.Experience with Kubernetes and KubeFlow workloads.Familiarity with the Model Development Lifecycle and MLOps.Experience architecting cloud systems for security, availability, performance, scalability, and cost.Ability to move fast in an environment with ambiguity and competing priorities.Experience at tech and product-driven companies/startups.Ability to iterate rapidly with researchers and engineers to improve product experience while building foundational capabilities.Experience with API security, observability, cloud access control and privacy best practices.Familiarity with deploying AI or ML models in demanding production environments.This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace.
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