This role pays more than
94%
of similar roles. Most pay
$181,906–$246,150
— the shaded band above.
At the midpoint, this role pays about
$268k
versus about
$214k
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 Senior Lead AI Engineer (MLX Emerging AI Patterns) within 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 AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch while implementing state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput. You must possess expertise in Python, Go, Scala, or Java to solve complex problems involving the development of high-performance AI infrastructure and the integration of advanced machine learning models into production systems for banking services.
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 Huggingface, VectorDBs, and PyTorch.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate complex scientific research into practical, high-performance production features.
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 and 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 and ML algorithms.
At least 6 years of experience programming with Python, Go, Scala, or Java.
7 years of experience deploying scalable and responsible AI solutions on cloud platforms like AWS, Google Cloud, or Azure.
Experience designing, developing, integrating, delivering, 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 with the ability to articulate complex AI concepts clearly to peers.
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
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability