Staff Applied Researcher

Capital One

. Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered banking products .

Posted 10/5/2026full-timeUnited StatesLead💰 $306,300 - $381,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and delivering AI foundation models, leveraging advanced methodologies and technologies such as PyTorch and AWS. Proven ability to translate complex research into actionable business goals while mentoring applied scientists and guiding research directions.

Highest-signal resume keywords

PhD In Relevant FieldsDeep Learning Model DevelopmentAI Methodologies ExpertiseHands-On Experience With Open-Source ToolsTrack Record Of High-Quality Machine Learning Ideas

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Applied ResearchTraining OptimizationSelf-Supervised LearningRobustnessExplainabilityReinforcement Learning From Human FeedbackLarge Language Model DevelopmentData PreparationModel EvaluationModel Validation

Soft Skills

MentoringCollaborationCommunication

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningCloud Computing Platforms

Industry Keywords

AI-Powered Banking ProductsApplied ScienceMachine LearningResearch AgendaLarge Deep Learning Models

Tech Stack

Tools & technologies

AWSCloudPyTorch

About the role

Key responsibilities & impact

Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered banking products
Leverage PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and related technologies to analyze large numeric and textual datasets
Build AI foundation models through design, training, evaluation, validation, and implementation
Conduct applied research and advance AI developments into customer experiences
Translate complex research into tangible business goals
Define and steward novel research directions for the organization’s long-term scientific agenda
Guide and mentor applied scientists and their managers without direct people-management responsibility
Collaborate with Applied Science, Engineering, Product, research communities, and prominent faculty members

Requirements

What you’ll need

PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research, OR M.S. in those fields plus 6 years of experience in Applied Research
Deep understanding of the foundations of AI methodologies
Experience building large deep learning models across language, images, events, or graphs
Expertise in one or more of training optimization, self-supervised learning, robustness, explainability, or RLHF
Track record of delivering models at scale in training data and inference volumes
Experience delivering libraries, platform-level code, or solution-level code to existing products
Track record of high-quality machine learning ideas, demonstrated through accomplishments such as first-author publications or projects
Ability to own and pursue a research agenda and autonomously carry out long-running projects
Hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms
Preferred: PhD in relevant fields; LLM/NLP, large language model, GPU cluster, recommender systems, optimization, fine-tuning, data preparation, and open-source framework experience as specified

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Employment authorization sponsorship considered for a new qualified applicant
Reasonable accommodations for applicants who require them