This role pays more than
84%
of similar roles. Most pay
$175,300–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
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
998 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 992 roles with salary data.
Sr. Lead AI Engineer (Inference Optimization, FM hosting, AI Platform) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary solutions that power core business functions. This role involves designing, testing, and supporting critical software components including foundation model training, large language model inference, similarity search, guardrails, and observability. The engineer will invent state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. The technical stack includes PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. Candidates must possess expertise in Python, Go, Scala, or Java, along with a strong foundation in engineering and mathematics to solve complex problems regarding high-performance AI infrastructure. This role focuses on building scalable, responsible AI systems that provide real-time, personalized experiences within the banking sector.
Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
Implement state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput of production systems.
Develop infrastructure for similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Utilize a broad stack of technologies including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate complex scientific research into practical, production-ready AI solutions.
Lead and mentor an engineering team while influencing cross-functional stakeholders.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 6 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 4 years of experience developing AI/ML algorithms.
At least 6 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, and supporting complex AI systems 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.
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders.
Excellent communication skills to articulate complex AI concepts clearly to peers.