This role pays more than
84%
of similar roles. Most pay
$184,975–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$216k
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.
As a Senior Lead AI Engineer (MLXT) within the Intelligent Foundations and Experiences team, you will drive critical technical initiatives to transform business analysis experiences in a highly regulated environment. You will modernize the core Analyst and AIML workflow orchestration layer by integrating frontier generative AI capabilities and self-serve tools to enable low-code or no-code development for domain experts. Your daily work involves building agentic-driven infrastructure, scaling managed AutoML offerings for tabular and time-series data, and engineering automated governance frameworks. To succeed, you must possess a strong foundation in engineering and mathematics while utilizing Python, Go, Scala, Java, C++, or C#. You will apply state-of-the-art techniques like LLM inference, similarity search, and vector databases to optimize training and inference software for improved hardware utilization, latency, and throughput.
Modernize the orchestration layer and user interface with generative AI capabilities and self-serve tooling.
Develop low-code and no-code tools to democratize AI development for business domain experts.
Build reliable, scalable, and secure agentic infrastructure that adheres to enterprise guardrails.
Scale enterprise-grade managed AutoML offerings for tabular and time-series data to reduce time-to-market.
Engineer automated governance frameworks and cutting-edge components for the core marketplace.
Optimize training and inference software to improve hardware utilization, latency, throughput, and cost.
Translate complex scientific research into production-ready AI systems and technologies.
What we're looking for
A Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field is required.
A Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field is accepted as an alternative to a Bachelor's.
Candidates with a Bachelor's degree must have at least 6 years of experience developing AI and ML algorithms or technologies.
Candidates with a Master's degree must have at least 4 years of experience developing AI and ML algorithms or technologies.
At least 6 years of experience programming with Python, Go, Scala, or Java is required.
Preferred experience includes 7 years of deploying scalable and responsible AI solutions on cloud platforms like AWS, Google Cloud, or Azure.
Experience in designing, developing, and supporting complex AI systems including LLM inference, similarity search, vector databases, and guardrails is preferred.
Demonstrated ability to lead engineering teams, mentor others, and influence cross-functional stakeholders is preferred.
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