This role pays more than
87%
of similar roles. Most pay
$182,500–$246,000
— the shaded band above.
At the midpoint, this role pays about
$262k
versus about
$214k
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
836 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 829 roles with salary data.
Staff AI Engineer joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance customer interactions and internal workflows. This role involves designing, testing, and supporting software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and observability. The engineer will implement optimization techniques for performance, scalability, cost, and latency while establishing enterprise-wide architecture standards and governance. The technical stack includes Python, Go, Scala, CUDA, Java, C++, C#, PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position focuses on the core challenge of building responsible, scalable AI infrastructure to solve complex problems in the banking sector. Candidates must possess strong engineering and mathematics foundations to navigate research-to-production transitions while ensuring transparency and fairness across all high-performance production systems.
What does a AI Engineer earn in California?
Median $246150 from 70 postings across 11 companies.
Develop and support AI software components including foundation model training, LLM inference, and multi-agent workflows.
Implement optimization techniques to improve performance, scalability, cost, latency, and throughput for large-scale production systems.
Design and integrate model routing, caching, and orchestration systems for hybrid and multi-model workloads.
Establish enterprise-wide AI architecture standards for tooling, observability, and deployment across multiple teams.
Integrate responsible AI principles including transparency, reproducibility, and fairness into all system designs.
Translate latest research and scientific publications into practical production features and technologies.
Lead internal education and mentorship through architecture councils and AI guilds.
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/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI/ML algorithms.
At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience designing AI systems with trade-offs regarding 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/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 (preferred).
Python
Go
Scala
CUDA
C++
C#
Java
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Model Evaluation
Model Optimization
Machine Learning
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Multi-agent Workflows
Similarity Search
Model Evaluation
Observability
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering