This role pays more than
99%
of similar roles. Most pay
$177,250–$241,750
— the shaded band above.
At the midpoint, this role pays about
$328k
versus about
$210k
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
936 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 933 roles with salary data.
As a Staff Applied Researcher on the AI Foundations team, you will serve as an individual contributor leader who guides and mentors applied scientists while representing the organization in the broader research community. You will partner with cross-functional teams of data scientists, software engineers, and product managers to build AI foundation models through every phase of development, including design, training, evaluation, and implementation. Your daily work involves leveraging a technical stack featuring PyTorch, AWS Ultraclusters, Huggingface, and Lightning to extract insights from massive volumes of numeric and textual data. You will solve complex problems by translating advanced research into tangible business goals and scalable production systems. The role focuses on the core challenge of developing high-performance AI infrastructure and innovative models to improve how customers interact with their money through automated, intelligent experiences.
Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
Partner with cross-functional teams of engineers and product managers to deliver AI-powered customer products.
Translate complex technical research into tangible business goals for stakeholders.
Define and steward novel research directions to expand the organization's long-term scientific agenda.
Represent Capital One in the research community by collaborating with prominent academic faculty members.
Mentor a team of applied scientists and their managers on technical projects and career growth.
Analyze large volumes of numeric and textual data using tools like PyTorch, Hugging Face, and AWS.
Evaluate emerging technologies and state-of-the-art methods to integrate them into next-generation customer experiences.
What we're looking for
PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research.
M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research.
Experience building large deep learning models and expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
Track record of delivering models at scale for both training data and inference volumes.
Experience delivering libraries, platform-level code, or solution-level code to existing products.
Proven track record of high-quality research ideas in machine learning, such as first-author publications or significant projects.
Ability to own a research agenda, including selecting impactful problems and autonomously managing long-running projects.
Experience with large scale deep learning based recommender systems (preferred); experience with production real-time and streaming environments (preferred).