This role pays more than
65%
of similar roles. Most pay
$167,500–$254,750
— the shaded band above.
At the midpoint, this role pays about
$234k
versus about
$211k
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.
As an Applied Researcher 4 on the AI Foundations team, you will collaborate with cross-functional teams of data scientists, software engineers, and product managers to develop AI-powered products for banking services. You will build AI foundation models through every phase of development, including design, training, evaluation, validation, and implementation. Your daily work involves uncovering insights within massive volumes of numeric and textual data while translating complex research into tangible business goals. To achieve these objectives, you will utilize a technical stack featuring PyTorch, AWS Ultraclusters, Huggingface, and Lightning. The role focuses on the core challenge of applying state-of-the-art AI to create real-time, intelligent, and automated customer experiences. You will also contribute to internal tech reports or conference submissions regarding novel methods in fields such as training optimization, self-supervised learning, robustness, explainability, and RLHF.
Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
Translate complex technical research into tangible business goals for stakeholders and product managers.
Conduct high-impact applied research to integrate state-of-the-art AI developments into customer experiences.
Develop production-ready code for large-scale models using PyTorch, Hugging Face, and cloud computing platforms.
Analyze and extract insights from massive volumes of numeric and textual data.
Prepare internal technical reports or conference submissions summarizing novel research methods and findings.
Identify and solve complex, undefined problems by researching and evaluating emerging technologies.
What we're looking for
Must have a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field.
Must have an M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field plus 2 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 an engineering mindset with a track record of delivering models at scale for both training and inference.
Experience delivering libraries, platform-level code, or solution-level code to existing products is required.
A track record of high-quality machine learning ideas, such as first-author publications or significant projects, is required.
Ability to own a research agenda and autonomously carry out long-running projects is required.