This role pays more than
59%
of similar roles. Most pay
$167,537–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$207k
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 and Finetuning) joins the Intelligent Foundations and Experiences team to develop proprietary solutions that empower internal teams and enhance customer interactions. You will collaborate with a cross-functional team of engineers, research scientists, and product managers to design, develop, test, deploy, and support critical AI software components. Key responsibilities include foundation model training, large language model inference, similarity search, guardrails, model evaluation, and observability. The role requires implementing state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. You will utilize a technical stack including PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. Required skills include proficiency in Python, Go, Scala, or Java, alongside expertise in hardware, software, and AI to solve complex problems within the banking domain.
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 Huggingface, VectorDBs, PyTorch, 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.
Build and deploy proprietary AI solutions that provide scalable value to millions of customers.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 4 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 2 years of experience developing AI and 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 such as AWS, Google Cloud, or Azure.
Experience designing, developing, delivering, and supporting AI services including LLM inference, similarity search, and vector databases.
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.
Strong foundation in engineering and mathematics to identify and exploit optimization opportunities in hardware and software.