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Capital One

Applied Researcher 5

Capital One

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

Posted 9/30/2026full-timeUnited StatesJuniorMid-Level💰 $262,500 - $326,800 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 applied research. Proven ability to translate complex AI concepts into actionable business outcomes while leading cross-functional teams.

Highest-signal resume keywords
PhD In Electrical EngineeringDeep Learning Model DevelopmentApplied Research ExperienceAI Methodologies ExpertiseExperience With Large Language Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Deep LearningMachine LearningTraining OptimizationSelf-Supervised LearningRobustnessExplainabilityReinforcement Learning From Human FeedbackModel CompressionTransfer LearningModel Adaptation
Soft Skills
LeadershipCollaborationResearch Agenda OwnershipCommunication
Tools & Technologies
PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms
Industry Keywords
Applied ResearchAI-Powered ProductsNLPPublications In Deep LearningModel Deployment

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 volumes of numeric and textual data
  • Build AI foundation models through design, training, evaluation, validation, and implementation
  • Conduct applied research to advance AI developments into customer experiences
  • Translate complex research into tangible business goals
  • Lead cross-functional research threads bridging prototype model development and deployment with ML engineering partners
  • Ensure scientific insights translate into production impact

Requirements

What you’ll need
  • Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with the exception that the required degree will be obtained on or before the scheduled start date, plus 2 years of experience in Applied Research
  • Alternatively, M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research
  • Deep understanding 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, 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: LLM PhD focus on NLP or Master's with 5 years of industrial NLP research experience
  • Preferred: Multiple publications related to pre-training large language models
  • Preferred: Experience training a large language model from scratch with 10B+ parameters and 500B+ tokens
  • Preferred: Publications in deep learning theory and at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR
  • Preferred: PhD focused on optimization of very large deep learning models
  • Preferred: Experience with model sparsification, quantization, training parallelism/partitioning, gradient checkpointing, or model compression
  • Preferred: Experience optimizing training for a 10B+ model
  • Preferred: Deep knowledge of deep learning algorithms or optimizer design
  • Preferred: Experience with compiler design
  • Preferred: PhD focused on fine-tuning LLMs
  • Preferred: Knowledge of transfer learning, model adaptation, and model guidance
  • Preferred: Experience deploying a fine-tuned large language model
  • Proven ability to design and lead small-scale research initiatives and guide junior researchers or engineers
  • 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 supporting total well-being
  • Reasonable accommodations for applicants who require them