This role pays more than
85%
of similar roles. Most pay
$180,000–$251,000
— the shaded band above.
At the midpoint, this role pays about
$262k
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.
Staff AI Engineer (Remote Eligible) 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, 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. Key technologies include PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. Candidates must possess strong skills in Python, Go, Scala, or Java, alongside a deep understanding of mathematics and engineering. The role focuses on solving complex technical challenges within the banking domain by building scalable, high-performance AI infrastructure to improve how customers interact with financial services.
What does a AI Engineer earn in California?
Median $246150 from 84 postings across 12 companies.
Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement technical solutions for similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Apply state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput of production systems.
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 engineering solutions for large-scale production environments.
What we're looking for
Bachelor's degree in Computer Science, Engineering, or AI with 8 years of experience developing AI/ML algorithms, or a Master's degree with 6 years of experience.
At least 8 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 architecting, designing, developing, and supporting complex AI systems.
Expertise in LLM inference, similarity search, vector databases, and guardrails using various programming languages.
Experience applying state-of-the-art techniques to optimize training and inference for hardware utilization, latency, throughput, and cost.
Ability to lead and mentor multiple engineering teams while influencing cross-functional stakeholders.
Strong communication skills to articulate complex AI concepts to peers and stakeholders.