This role pays more than
96%
of similar roles. Most pay
$172,500–$239,550
— the shaded band above.
At the midpoint, this role pays about
$288k
versus about
$206k
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.
Staff AI Engineer
As part of the Intelligent Foundations and Experiences team, you will collaborate with cross-functional partners to develop and deploy proprietary AI solutions that enhance internal workflows and customer interactions. You will design, test, and support critical software components including foundation model training, large language model inference, similarity search, guardrails, and observability systems. The role involves implementing state-of-the-art LLM optimization techniques to improve performance metrics like latency, throughput, and cost for large-scale production environments. You will utilize a technical stack featuring PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. Required skills include proficiency in Python, Go, Scala, or Java, alongside deep expertise in engineering and mathematics to solve complex problems within the banking domain. You will contribute to the long-term roadmap of foundational AI systems while translating scientific research into production-ready technologies.
What does a AI Engineer earn in California?
Median $246150 from 84 postings across 12 companies.
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, high-performance production features.
Partner with cross-functional teams to deliver AI-powered products for internal operations and customer interactions.
What we're looking for
A Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field is required.
A Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field is accepted as an alternative to a Bachelor's.
Candidates with a Bachelor's degree must have at least 8 years of experience developing AI and ML algorithms or technologies.
Candidates with a Master's degree must have at least 6 years of experience developing AI and ML algorithms or technologies.
At least 8 years of experience programming with Python, Go, Scala, or Java is required.
Experience deploying scalable and responsible AI solutions on cloud platforms like AWS, Google Cloud, or Azure is preferred.
Experience architecting, designing, and supporting complex AI systems including LLM inference, similarity search, and vector databases is preferred.
Proven ability to lead engineering teams and communicate complex AI concepts to stakeholders is preferred.