This role pays more than
61%
of similar roles. Most pay
$164,250–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$205k
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 (MLX, Agentic AI, Gen AI platform Services) joins the Intelligent Foundations and Experiences team to develop proprietary solutions that empower internal teams and enhance customer interactions through advanced machine learning. You will collaborate with cross-functional partners to design, develop, test, deploy, and support critical software components including foundation model training, large language model inference, similarity search, guardrails, and observability. The role involves 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 featuring PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters while programming in Python, Go, Scala, or Java. This position focuses on building high-performance AI infrastructure to solve complex problems related to large-scale production systems and the development of responsible, scalable AI models for banking services.
Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, experimentation, governance, and observability for production systems.
Develop state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput.
Utilize a broad stack of open-source and SaaS technologies including 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.
Partner with cross-functional teams to deliver AI-powered products for internal use and customer interaction.
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/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/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.
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability