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 and deploy proprietary AI solutions that enhance internal workflows and customer interactions. 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 implement state-of-the-art LLM optimization techniques to improve performance metrics like latency, throughput, and cost for large-scale production systems. Key technologies include PyTorch, Huggingface, Nemo Guardrails, VectorDBs, and AWS Ultraclusters. Candidates must possess expertise in Python, Go, Scala, or Java to build scalable infrastructure. The work focuses on the technical challenge of creating responsible, high-performance AI systems within the banking sector, specifically addressing the need for reliable, automated tools that simplify complex financial services and improve overall user experience.
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.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate complex scientific research into practical, high-performance production features.
Partner with cross-functional teams to deliver AI-powered products for internal and external users.
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 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 with expertise in hardware, software, and AI systems.
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability