Staff Applied Researcher

Capital One

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

Posted 9/21/2026full-timeUnited StatesLead💰 $306,300 - $381,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing AI foundation models using advanced methodologies and tools, while effectively translating research into actionable business strategies. Proven ability to lead and mentor teams in applied research and collaborate with cross-functional stakeholders to drive innovation in AI products.

Highest-signal resume keywords

PhD In Computer ScienceDeep Learning Model DevelopmentExperience With PyTorchApplied Research ExperienceAI Methodologies Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Foundation Model DevelopmentTraining OptimizationSelf-Supervised LearningModel ExplainabilityReinforcement Learning From Human FeedbackLarge Scale Model DeliveryMachine Learning LibrariesData AnalysisModel CompressionGradient Checkpointing

Soft Skills

CollaborationMentoringResearch Agenda OwnershipCommunication

Tools & Technologies

AWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing PlatformsPyTorch GeometricDGL

Industry Keywords

Applied ResearchAIMachine LearningDeep LearningData QualityDataset CurationLarge Open-Source Corpora

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, 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 bring the latest AI developments into customer experiences
Translate complex research into tangible business goals
Define and steward novel research directions that expand Capital One’s long-term scientific agenda
Drive strategic direction through collaboration with Applied Science, Engineering, and Product leaders
Guide and mentor applied scientists and their managers without direct people-management responsibility
Represent Capital One externally in the AI research community and collaborate with prominent faculty

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 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 high-quality machine learning ideas, demonstrated by 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 Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or related fields
Preferred: experience with geometric deep learning, graph neural networks, sequential models, multivariate time series, large-scale recommender systems, production real-time and streaming environments, PyTorch Geometric, DGL, model optimization, fine-tuned large language models, transfer learning, model adaptation, tokenization, data quality, dataset curation, labeling, and large open-source corpora
Preferred: 5+ years of experience and/or publications in model sparsification, quantization, training parallelism/partitioning design, gradient checkpointing, or model compression
Demonstrated history of initiating and leading multi-year AI/ML research programs
Capital One will consider sponsoring a new qualified applicant for employment authorization

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 that support total well-being
Reasonable accommodations for applicants who require them