Applied Researcher 5

Capital One

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

Posted 9/24/2026full-timeUnited StatesJuniorMid-Level💰 $262,500 - $326,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing AI foundation models and solutions, leveraging advanced methodologies and tools such as PyTorch and AWS. Proven ability to translate complex research into impactful business applications while leading cross-functional teams in applied research.

Highest-signal resume keywords

PhD In Electrical Engineering, Computer Engineering, Computer Science, AI, MathematicsExperience In Applied ResearchHands-On Experience Developing AI Foundation ModelsExpertise In Training Optimization, Self-Supervised Learning, RobustnessTrack Record Of Delivering Models At Scale

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Foundation Model DevelopmentDeep Learning Model BuildingTraining OptimizationSelf-Supervised LearningRobustnessExplainabilityReinforcement Learning From Human FeedbackModel CompressionTransfer LearningModel Adaptation

Soft Skills

Autonomous Research Agenda OwnershipCross-Functional CollaborationEffective Communication

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchMachine LearningNatural Language ProcessingDeep Learning TheoryModel SparsificationQuantizationTraining ParallelismGradient CheckpointingPublications In AI Conferences

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 related 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, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with the required degree obtained by the scheduled start date, plus 2 years of experience in Applied Research; or an M.S. in those 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 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 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 autonomously
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: 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: Optimization-focused PhD or experience/publications in model sparsification, quantization, training parallelism, gradient checkpointing, or model compression
Preferred: Experience optimizing training for a 10B+ model
Preferred: Deep knowledge of deep learning algorithmic and/or optimizer design
Preferred: Experience with compiler design
Preferred: Fine-tuning-focused PhD or 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 accommodation support for applicants
Equal opportunity and non-discrimination commitment
Drug-free workplace