Applied Researcher I – AI Foundations, VLM

Capital One

Applied researcher building large AI foundation models and VLM solutions for Capital One’s banking products. Advancing applied research from model design through production implementation.

Posted 9/2/2026full-timeNew York City • California, Massachusetts, New York, Virginia • 🇺🇸 United StatesJuniorMid-Level💰 $218,700 - $272,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing AI foundation models, with a strong focus on deep learning methodologies and large-scale model deployment. Proven ability to translate complex AI concepts into actionable business strategies while collaborating with cross-functional teams.

Highest-signal resume keywords

PhD In Electrical EngineeringDeep Learning Model DevelopmentAI Methodology FoundationsExperience With PyTorchNLP Research Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Training OptimizationSelf-Supervised LearningRobustnessExplainabilityReinforcement Learning From Human FeedbackLarge Language Model TrainingModel AdaptationModel GuidanceCompiler DesignDeep Learning Theory

Soft Skills

Problem SolvingCollaborationTalent Development

Tools & Technologies

AWS UltraclustersHugging FaceLightningVectorDBsOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchMachine LearningNatural Language ProcessingAI-Powered ProductsEmerging Technologies

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
Use PyTorch, AWS Ultraclusters, Hugging Face, Lightning, VectorDBs, and other technologies to uncover insights from large numeric and textual datasets
Build AI foundation models through design, training, evaluation, validation, and implementation
Conduct applied research and advance emerging AI developments into customer experiences
Translate complex technical work into tangible business goals
Research and evaluate emerging technologies and state-of-the-art AI methods
Define and solve ambiguous problems and improve the status quo with stakeholders
Contribute to talent development

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; required degree may be obtained on or before the scheduled start date
Alternatively, an M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research
Deep understanding of AI methodology foundations
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 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, 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 a related technical field
Preferred: NLP focus or Master's degree with 5 years of industrial NLP research experience
Preferred: publications related to pre-training large language models, deep learning theory, or major ML conferences
Preferred: experience training a large language model from scratch with 10B+ parameters and 500B+ tokens
Preferred: experience optimizing training for a 10B+ model
Preferred: deep-learning algorithmic or optimizer design knowledge
Preferred: compiler design experience
Preferred: knowledge of transfer learning, model adaptation, and model guidance
Preferred: experience deploying a fine-tuned large language model
Capital One will consider sponsoring a new qualified applicant for employment authorization

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
Reasonable accommodations for applicants who require them
Equal opportunity and non-discrimination commitment
Drug-free workplace