Applied Researcher 4 – AI Foundations, LLM, Optimization, Finetuning

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 building and optimizing AI foundation models, with a strong focus on deep learning methodologies and large-scale model deployment. Proven ability to translate complex research into actionable business outcomes 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, RobustnessTrack Record Of Delivering Models At ScaleHands-On Experience Developing AI Foundation Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep LearningAI MethodologiesModel OptimizationNatural Language ProcessingModel CompressionTraining ParallelismQuantizationTransfer LearningFine-TuningRobustness

Soft Skills

CollaborationResearch Agenda OwnershipAutonomous Project Management

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchMachine LearningLarge Language ModelsDeep Learning TheoryTechnical 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
Leverage PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and other technologies to analyze numeric and textual data
Build AI foundation models through design, training, evaluation, validation, and implementation
Conduct applied research and advance AI developments into next-generation customer experiences
Translate complex research into tangible business goals
Collaborate with senior researchers to prepare internal technical reports or conference submissions on novel methods or findings

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 these 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, 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 technical field
Preferred: LLM PhD focus on NLP or Master’s with 5 years of industrial NLP research experience
Preferred: Multiple publications related to large language model pre-training
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 PhD focused on optimizing training of very large deep learning models
Preferred: Multiple years of experience and/or publications in 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 and/or optimizer design
Preferred: Experience with compiler design
Preferred: Finetuning PhD focused on guiding LLMs with further tasks
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
Employment authorization sponsorship may be considered for a new qualified applicant
Reasonable accommodations for applicants with disabilities