This role pays more than
59%
of similar roles. Most pay
$172,900–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$210k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
998 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 992 roles with salary data.
Lead AI Engineer (AI Foundations) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary solutions that power core business functions. You will collaborate with cross-functional teams of engineers, research scientists, and product managers to build AI-powered products while contributing to the long-term roadmap of foundational systems. Daily responsibilities include designing, testing, and supporting software components such as foundation model training, large language model inference, similarity search, guardrails, evaluation, and observability. You will implement state-of-the-art LLM optimization techniques to improve performance metrics like latency, throughput, and cost for production systems. The role requires proficiency in Python, Go, Scala, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. This position addresses the technical challenge of creating scalable, high-performance AI infrastructure to enhance customer interactions and internal workflows within the banking sector.
Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement infrastructure for similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Develop state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput of production systems.
Utilize a broad stack of open-source and SaaS technologies including Huggingface, VectorDBs, PyTorch, and AWS Ultraclusters.
Translate scientific research and academic publications into practical, high-performance production AI solutions.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
Solve complex, undefined problems by identifying root causes and communicating findings clearly to cross-functional teams.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 4 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 2 years of experience developing AI/ML algorithms.
At least 4 years of experience programming with Python, Go, Scala, or Java.
Experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, or Azure.
Experience designing, developing, delivering, and supporting AI services.
Experience developing AI/ML technologies including LLM inference, similarity search, vector databases, and guardrails.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Ability to interpret scientific publications and apply novel research techniques in production environments.