This role pays less than
53%
of similar roles. Most pay
$192,050–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$219k
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 (FM Hosting, LLM Inference) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary solutions that power core business functions. This role involves collaborating with cross-functional teams of engineers, research scientists, and product managers to build AI-powered products. The engineer will design, test, and support software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, and observability. Key responsibilities include implementing state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. The role requires proficiency in Python, Go, Scala, or Java, along with experience using tools such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch. This position focuses on the technical challenge of building high-performance AI infrastructure to solve complex problems within the banking domain.
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, Nemo Guardrails, and PyTorch.
Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.
Translate complex scientific publications into practical, high-performance production features for banking services.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 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 like AWS, Google Cloud, or Azure.
Experience designing, developing, delivering, and supporting AI services.
Experience developing AI and 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 understand scientific publications and apply novel research techniques in production environments.