Applied Researcher 4 – AI Foundations, LLM Core, Agentic AI

Capital One

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

Posted 9/18/2026full-timeNew York City • California • 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 applied research. Proven ability to translate complex AI concepts into actionable business strategies while collaborating effectively with cross-functional teams.

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

Deep LearningMachine LearningAI MethodologiesModel OptimizationNatural Language ProcessingModel CompressionTransfer LearningQuantizationTraining ParallelismGradient Checkpointing

Soft Skills

CollaborationResearch Agenda OwnershipAutonomous Project Management

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchAI-Powered ProductsCustomer ExperienceLarge Language ModelsPublications In Deep Learning

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 next-generation customer experiences
Translate complex research into tangible business goals
Collaborate with senior researchers on internal technical reports or conference submissions summarizing novel methods or findings
Apply AI and machine learning to improve customer experiences and banking products at Capital One

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 degree obtained on or before the scheduled start date; or an M.S. in those fields plus 2 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 or improvements, demonstrated through 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 technical field
Preferred: PhD focus on NLP or master's degree with 5 years of industrial NLP research experience
Preferred: Multiple publications on pre-training large language models
Preferred: Participation in 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: 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 algorithmic or optimizer design
Preferred: Experience with compiler design
Preferred: PhD focus on guiding LLMs with further tasks such as supervised fine-tuning, instruction-tuning, dialogue fine-tuning, or parameter tuning
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 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 with disabilities