This role pays more than
57%
of similar roles. Most pay
$170,875–$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 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning) joins the Intelligent Foundations and Experiences team to develop proprietary solutions that power core business functions. You will collaborate with cross-functional teams of engineers, research scientists, and product managers to design, develop, test, deploy, and support critical AI software components. Your daily work involves foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. To achieve these goals, you will utilize a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch while implementing optimization techniques for performance, scalability, cost, latency, and throughput. The role focuses on the core challenge of building scalable, high-performance AI infrastructure to provide reliable, real-time customer experiences within the banking sector using Python, Go, Scala, Java, or C++.
Design, develop, test, deploy, and support 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 Huggingface, VectorDBs, PyTorch, and AWS Ultraclusters.
Translate scientific research into practical, production-ready AI solutions and novel technical applications.
Contribute to the technical vision and long-term roadmap for foundational AI systems.
Build scalable and responsible AI products that enhance internal workflows and customer interactions.
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.