Applied Researcher 4 – AI Foundations, Recommendation Systems

Capital One

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

Posted 10/16/2026full-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 using advanced methodologies and open-source tools, with a strong focus on delivering scalable solutions and translating technical research into business applications.

Highest-signal resume keywords

PhD In Electrical EngineeringDeep Learning Model DevelopmentExperience With PyTorchLarge Language Model TrainingApplied Research Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI MethodologiesTraining OptimizationSelf-Supervised LearningModel CompressionGradient CheckpointingTransfer LearningModel AdaptationQuantizationTraining ParallelismRobustness

Soft Skills

CollaborationCommunicationAutonomous Research Agenda

Tools & Technologies

AWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchMachine LearningAI Foundation ModelsControlled ExperimentsPeer-Reviewed 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 large volumes of 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 technical work into tangible business goals
Collaborate with senior researchers to prepare internal technical reports or conference submissions describing 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; required degree must be obtained by the scheduled start date
Alternatively, an M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related 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
Experience and/or publications in LLM pre-training, optimization, finetuning, deep learning theory, model sparsification, quantization, training parallelism, gradient checkpointing, model compression, compiler design, transfer learning, model adaptation, and model guidance
Experience optimizing training for a 10B+ model
Demonstrated ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks
Experience designing controlled experiments and documenting reproducibility results
Preferred qualifications include relevant PhD focus, publications, large language model training experience, and conference publications at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR
Capital One will consider sponsoring employment authorization for a new qualified applicant

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 who require them
Equal opportunity and non-discrimination protections