This role pays more than
85%
of similar roles. Most pay
$177,262–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$212k
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.
As a Sr. Lead AI Engineer (AI Foundations) within the Intelligent Foundations and Experiences team, you will partner with cross-functional teams of engineers, research scientists, and product managers to deliver AI-powered products. You will design, develop, test, deploy, and support critical software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. To achieve these goals, you will utilize a technical stack featuring AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch while implementing state-of-the-art LLM optimization techniques to improve performance metrics like latency and throughput. The role focuses on the core challenge of building scalable, high-performance AI infrastructure and proprietary solutions that provide responsible machine learning capabilities for banking services. Required skills include proficiency in Python, Go, Scala, or Java, along with a strong foundation in engineering and mathematics.
Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, and observability for production AI systems.
Develop state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput.
Utilize a 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 complex scientific research into practical, high-performance production features.
Lead and mentor engineering teams while influencing cross-functional stakeholders on AI initiatives.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI and ML algorithms.
At least 6 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, integrating, delivering, and supporting complex AI systems including LLM inference and vector databases.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders.
Excellent communication skills with the ability to articulate complex AI concepts to peers.