This role pays more than
85%
of similar roles. Most pay
$172,112–$250,250
— the shaded band above.
At the midpoint, this role pays about
$262k
versus about
$211k
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
1435 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 702 roles with salary data.
Staff AI Engineer joins the Intelligent Foundations and Experiences team to develop responsible, scalable AI systems for banking applications. This role involves designing, developing, testing, and deploying critical software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and observability frameworks. The engineer will establish enterprise-wide architecture standards, optimize performance metrics like latency and throughput, and manage model routing and orchestration for hybrid workloads. Technical requirements include proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position focuses on solving complex problems related to high-performance AI infrastructure and ensuring fairness-by-design. Candidates must be able to translate scientific research into production environments while managing the technical roadmap for large-scale systems that enhance customer interactions and internal workflows.
What does a AI Engineer earn in California?
Median $246150 from 75 postings across 11 companies.
Develop and support AI software components including foundation model training, LLM inference, agentic workflows, and guardrails.
Implement state-of-the-art optimization techniques to improve performance, scalability, cost, and latency for large-scale production systems.
Define the technical direction and long-term roadmap for enterprise-wide foundational AI architecture and infrastructure.
Design and integrate model routing, caching, and orchestration systems for hybrid and multi-model workloads.
Establish corporate standards for AI governance, observability, evaluation frameworks, and responsible AI principles.
Translate complex scientific research into production-ready features by applying novel techniques to real-world problems.
Lead internal education and mentorship through architecture councils and AI guilds to share best practices.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 8 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI and ML algorithms.
At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience designing AI systems with tradeoff decisions around cost, latency, throughput, and accuracy (preferred).
8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems (preferred).
Experience developing AI and ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost (preferred).
Remote (San Francisco, CA)+47 days ago
$286,200–$326,700
Machine Learning
Python
Go
Scala
CUDA
C++
Java
PyTorch
Huggingface
VectorDBs
AWS
Google Cloud
Azure
LLM Inference
Agentic Workflows
Similarity Search
Model Evaluation
Observability