This role pays more than
57%
of similar roles. Most pay
$171,500–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$209k
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.
Lead AI Engineer (Vision model customization, VLM) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance internal workflows and customer interactions. This role involves designing, testing, and supporting software components including foundation model training, large language model inference, similarity search, guardrails, and model evaluation. 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 be proficient in Python, Go, Scala, or Java, with experience in C++ or C# preferred. The role focuses on the technical challenge of building scalable, high-performance AI infrastructure and applying novel research to solve complex problems within the banking domain through advanced machine learning engineering.
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 PyTorch, Hugging Face, VectorDBs, and AWS Ultraclusters.
Translate scientific research into practical, production-ready AI solutions for banking products.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Solve complex, undefined problems by identifying and addressing root causes in large-scale infrastructure.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI/ML algorithms.
At least 4 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, delivering, and supporting AI services.
Experience developing AI and ML technologies including LLM inference, similarity search, vector databases, and guardrails.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Ability to interpret scientific publications and apply novel research techniques in production environments.