Applied Researcher 5

Capital One

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

Posted 11/4/2026full-timeUnited StatesJuniorMid-Level💰 $262,500 - $326,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI foundation models, leveraging advanced methodologies in deep learning and natural language processing. Proven ability to translate complex research into impactful business solutions while collaborating with cross-functional teams.

Highest-signal resume keywords

PhD In Electrical EngineeringDeep Learning Model DevelopmentApplied Research ExperienceAI Methodologies ExpertiseExperience With PyTorch

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep LearningNatural Language ProcessingTraining OptimizationSelf-Supervised LearningModel CompressionModel SparsificationGradient CheckpointingRobustnessExplainabilityTransfer Learning

Soft Skills

CollaborationResearch Agenda OwnershipProblem-Solving

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchMachine Learning EngineeringLarge Language ModelsModel AdaptationTraining Data Optimization

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 apply emerging AI developments to 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 required degree 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 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, select impactful research problems, 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 degree with 5 years of industrial NLP research experience
Preferred: Multiple publications related to pre-training large language models
Preferred: Membership on a team that trained 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 optimizing training of very large deep learning models
Preferred: Experience 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: 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
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 that support total well-being
Employment authorization sponsorship consideration for a new qualified applicant
Reasonable accommodations for applicants with disabilities