This role pays less than
65%
of similar roles. Most pay
$177,262–$246,150
— the shaded band above.
At the midpoint, this role pays about
$192k
versus about
$212k
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
1042 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1036 roles with salary data.
As a Lead AI Engineer (MLX Emerging AI Patterns) on the Intelligent Foundations and Experiences team, you will partner with cross-functional teams of engineers, research scientists, and product managers to deliver AI-powered products. You will design, develop, test, deploy, and support critical software components including 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 featuring PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters while implementing state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput. You will work within the banking domain to build high-performance AI infrastructure and proprietary solutions that enhance how customers interact with financial services. Required skills include proficiency in Python, Go, Scala, or Java, alongside a strong foundation in engineering and mathematics.
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 open-source and SaaS technologies including PyTorch, Hugging Face, and VectorDBs.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate complex scientific research into practical, high-performance production features.
Build scalable and responsible AI solutions on cloud platforms like AWS.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 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 plus at least 2 years of experience developing AI and ML algorithms.
At least 4 years of experience programming with Python, Go, Scala, or Java.
6 years of 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 algorithms such as LLM Inference, Similarity Search, VectorDBs, and Guardrails using Python, C++, C#, Java, or Golang.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Ability to understand scientific publications and apply novel research techniques in production environments.