This role pays more than
88%
of similar roles. Most pay
$193,001–$254,750
— the shaded band above.
At the midpoint, this role pays about
$281k
versus about
$224k
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
878 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 872 roles with salary data.
Applied Researcher 5 (AI Foundations, LLM Core and Agentic AI) joins the AI Foundations team to develop trustworthy and reliable AI systems for banking applications. This role involves partnering with cross-functional teams of data scientists and engineers to build AI foundation models through every phase of development, including design, training, evaluation, validation, and implementation. The researcher will translate complex scientific insights into tangible business goals while managing research threads that bridge prototype development and production deployment. Key technical requirements include proficiency in Pytorch, AWS Ultraclusters, Huggingface, and Lightning to analyze large volumes of numeric and textual data. Candidates must possess expertise in deep learning models, training optimization, self-supervised learning, robustness, explainability, or RLHF. The role focuses on solving the challenge of creating high-performance AI infrastructure to power automated customer experiences and intelligent financial services.
Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
Conduct high-impact applied research to integrate state-of-the-art AI developments into customer experience products.
Analyze large volumes of numeric and textual data using tools like PyTorch, Hugging Face, and AWS Ultraclusters.
Lead cross-functional research threads to bridge the gap between prototype model development and production deployment.
Translate complex technical research into tangible business goals for stakeholders and product managers.
Research and evaluate emerging technologies to identify opportunities for application in banking services.
Develop scalable models and solutions that handle high volumes of training data and inference requests.
Own and pursue a research agenda by selecting impactful problems and executing long-running projects autonomously.
What we're looking for
Must have a PhD in a relevant field with 2 years of experience or an MS degree with 4 years of experience in Applied Research.
Experience building large deep learning models for language, images, events, or graphs is required.
Expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF is required.
Must have a track record of delivering models at scale regarding both training data and inference volumes.
Experience delivering libraries, platform-level code, or solution-level code to existing products is required.
Proven ability to own a research agenda and independently carry out long-running projects is required.
A track record of high-quality machine learning ideas or improvements, such as first-author publications, is required.
Experience with LLM pre-training, optimization, or fine-tuning is preferred; multiple publications in top-tier venues like NeurIPS or ICML are preferred.