Applied Researcher 5

Capital One

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

Posted 10/27/2026full-timeUnited StatesJuniorMid-Level💰 $262,500 - $326,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing AI foundation models, leveraging advanced methodologies in deep learning and machine learning. Proven ability to translate complex research into actionable business outcomes while leading cross-functional teams and guiding junior researchers.

Highest-signal resume keywords

PhD In Electrical Engineering, Computer Engineering, Computer Science, AI, MathematicsExperience In Applied ResearchExpertise In Training Optimization, Self-Supervised Learning, Robustness, Explainability, RLHFHands-On Experience Developing AI Foundation Models Using Open-Source ToolsTrack Record Of Delivering Models At Scale

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep Learning ModelsAI MethodologiesModel OptimizationResearch DesignData AnalysisModel EvaluationModel ValidationModel ImplementationMachine Learning IdeasExperimental Design

Soft Skills

LeadershipCollaborationAutonomous Research PursuitCommunicationMentoring

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchGeometric Deep LearningGraph Neural NetworksRecommender SystemsStreaming EnvironmentsTokenizationData QualityDataset CurationModel CompressionPublications In KDD, ICML, NeurIPS, ICLR

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
Lead cross-functional research threads connecting prototype model development and deployment with ML engineering partners
Ensure scientific insights translate into production impact
Research and evaluate emerging technologies and state-of-the-art methods
Identify impactful research problems and autonomously pursue long-running research projects
Design and lead small-scale research initiatives, guiding junior researchers or engineers through experimental design and evaluation

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; or M.S. in those 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 or improvements, 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 relevant field
Preferred: behavioral models research in geometric deep learning, graph neural networks, sequential models, or multivariate time series
Preferred: publications at KDD, ICML, NeurIPS, or ICLR
Preferred: scaling graph models to more than 50m nodes
Preferred: large-scale deep learning recommender systems
Preferred: production real-time and streaming environments
Preferred: contributions to PyTorch Geometric or DGL
Preferred: new methods for inference or representation learning on graphs or sequences
Preferred: datasets with 100m+ users
Preferred: optimization of very large language model training
Preferred: 5+ years of experience and/or publications in model sparsification, quantization, training parallelism/partitioning, gradient checkpointing, or model compression
Preferred: fine-tuning large language models and knowledge of transfer learning, model adaptation, and model guidance
Preferred: publications or contributions involving tokenization, data quality, dataset curation, labeling, or open-source corpora/libraries
Proven ability to design and lead small-scale research initiatives and guide junior researchers or engineers
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position

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 who require them