This role pays more than
66%
of similar roles. Most pay
$168,450–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$207k
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
As part of the Intelligent Foundations and Experiences team, you will develop and deploy proprietary AI solutions that power core business functions and enhance customer interactions. You will collaborate with cross-functional teams to design, test, and support software components including foundation model training, large language model inference, similarity search, guardrails, and model evaluation. Your daily work involves implementing state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. You will utilize a technical stack featuring PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters while programming in Python, Go, Scala, or Java. This role focuses on the technical challenge of building responsible, high-performance AI infrastructure to solve complex problems in the banking sector by creating scalable systems that provide real-time, personalized experiences for customers and associates alike.
Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, experimentation, governance, and observability for production systems.
Develop state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput.
Utilize a broad stack of technologies including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate scientific research into practical production techniques for large-scale AI infrastructure.
Build and deploy proprietary AI solutions that provide scalable value to millions of customers.
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 and 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 and 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 including LLM inference, similarity search, and vector databases.
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.
Strong foundation in engineering and mathematics to identify and exploit optimization opportunities in hardware and software.