This role pays more than
78%
of similar roles. Most pay
$186,325–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$216k
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 (FM Hosting, LLM Inference) on 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, throughput, and cost. You will work within the banking domain to build scalable, high-performance AI infrastructure and proprietary solutions that enhance how customers interact with financial services. Required skills include proficiency in Python, Go, Scala, or Java, alongside deep expertise in hardware, software, and machine learning algorithms.
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 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 complex scientific research into practical, production-ready AI solutions.
Lead and mentor an engineering team while influencing cross-functional stakeholders.
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 like AWS, Google Cloud, or Azure.
Experience designing, developing, and supporting complex AI systems 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 lead and mentor an engineering team while influencing cross-functional stakeholders.
Strong communication skills to articulate complex AI concepts clearly to peers.