Applied Researcher II – AI Foundations, LLM Core, Agentic AI

Capital One

Applied researcher building large-scale AI foundation models for Capital One’s banking products. Advancing LLM, deep-learning, and agentic-AI capabilities from research through production.

Posted 8/21/2026full-timeNew York City • California, Massachusetts, New York, Virginia • 🇺🇸 United StatesJuniorMid-Level💰 $262,500 - $326,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing AI foundation models and solutions, leveraging advanced methodologies and cloud computing platforms. Proven ability to translate complex research into actionable business goals while leading impactful research agendas.

Highest-signal resume keywords

PhD In Electrical EngineeringAI Foundation Model DevelopmentDeep Learning Model BuildingApplied Research ExperienceTraining Optimization Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI MethodologiesLarge Deep Learning ModelsSelf-Supervised LearningRobustnessExplainabilityReinforcement Learning From Human FeedbackModel DeploymentTransfer LearningFine-TuningCompiler Design

Soft Skills

CollaborationProblem-SolvingTalent DevelopmentResearch Agenda Ownership

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningVectorDBs

Industry Keywords

Applied ResearchMachine LearningNatural Language ProcessingLarge Language Model TrainingDeep Learning Theory

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 products
Leverage PyTorch, AWS Ultraclusters, Hugging Face, Lightning, VectorDBs, and other technologies to analyze large numeric and textual datasets
Build AI foundation models through design, training, evaluation, validation, and implementation
Conduct applied research to advance AI developments into customer experiences
Translate complex research and technical work into tangible business goals
Research and evaluate emerging technologies and apply state-of-the-art methods
Challenge conventional thinking and collaborate with stakeholders to improve the status quo
Support talent development for the team and broader organization
Own and pursue a research agenda, including selecting impactful problems and carrying out long-running projects

Requirements

What you’ll need

Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with the required degree obtained on or before the scheduled start date, plus 2 years of experience in Applied Research
Alternatively, an M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research
Hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms
Deep understanding of the foundations of AI methodologies
Experience building large deep learning models for 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 new or improved machine-learning ideas, demonstrated through accomplishments such as first-author publications or projects
Ability to own and pursue a research agenda, choose impactful research problems, and autonomously carry out long-running projects
Preferred: PhD in a related technical field; LLM/NLP research; publications; large-language-model training; deep-learning theory; optimization; compiler design; fine-tuning; transfer learning; model deployment

Benefits

Comp & perks

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