Applied Researcher, Level 4

Capital One

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

Posted 9/21/2026full-timeUnited StatesJuniorMid-Level💰 $218,700 - $272,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI methodologies and the development of large deep learning models, with a strong focus on delivering AI-powered products and translating research into business applications. Proficient in using advanced tools and technologies for building and optimizing AI foundation models at scale.

Highest-signal resume keywords

PhD In Electrical Engineering, Computer Engineering, Computer Science, AI, MathematicsExperience Building Large Deep Learning ModelsExpertise In Training Optimization, Self-Supervised Learning, RobustnessHands-On Experience Developing AI Foundation ModelsTrack Record Of High-Quality Machine Learning Ideas

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI MethodologiesDeep Learning ModelsTraining OptimizationSelf-Supervised LearningModel SparsificationQuantizationGradient CheckpointingSupervised FinetuningTransfer LearningModel Compression

Soft Skills

CollaborationAutonomous Project ManagementResearch Agenda Ownership

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchLarge Language Model Pre-TrainingDeep Learning TheoryNLP ResearchConference Publications

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, 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 capabilities and customer experiences
Translate complex research into tangible business goals
Collaborate with senior researchers on internal technical reports and conference submissions

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; alternatively, an M.S. in these fields plus 2 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, demonstrated by accomplishments 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 field; LLM/NLP research focus or Master's with 5 years of industrial NLP research experience
Preferred: publications related to large language model pre-training, deep learning theory, or conferences including ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR
Preferred: experience training a large language model from scratch with 10B+ parameters and 500B+ tokens
Preferred: experience with model sparsification, quantization, training parallelism/partitioning, gradient checkpointing, or model compression
Preferred: experience optimizing training for a 10B+ model
Preferred: deep learning algorithmic and/or optimizer design knowledge
Preferred: compiler design experience
Preferred: experience with supervised finetuning, instruction-tuning, dialogue-finetuning, or parameter tuning
Preferred: knowledge of transfer learning, model adaptation, and model guidance
Preferred: experience deploying a fine-tuned large language model

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
Employment authorization sponsorship may be considered for a new qualified applicant
Reasonable accommodations for applicants with disabilities