This role pays less than
63%
of similar roles. Most pay
$172,900–$246,150
— the shaded band above.
At the midpoint, this role pays about
$192k
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 AI solutions that enhance products for millions of customers. This role involves collaborating with cross-functional teams to design, test, and support software components including foundation model training, large language model inference, similarity search, guardrails, evaluation, and observability. The engineer will implement state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. The technical stack includes Python, Go, Scala, Java, C++, C#, PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. This position focuses on the core challenge of building responsible, scalable, and high-performance AI infrastructure to solve complex problems in the banking sector by creating real-time, personalized customer experiences through advanced machine learning and engineering.
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 open-source and SaaS technologies including 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.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies.
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 and ML algorithms including LLM inference, similarity search, vector databases, and guardrails using Python, C++, C#, Java, or Golang.
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.