Applied Researcher 4 – AI Foundations, Multimodal Guardrails, VLM's

Capital One

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

Posted 10/8/2026full-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 training. 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, MathematicsDeep Learning Model DevelopmentAI Methodologies ExpertiseExperience With PyTorch And AWS UltraclustersTrack Record Of High-Quality Machine Learning Publications

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep LearningAI Foundation ModelsTraining OptimizationSelf-Supervised LearningModel CompressionQuantizationGradient CheckpointingSupervised Fine-TuningNLP ResearchTransfer Learning

Soft Skills

CollaborationAutonomous Research Agenda ManagementEffective Communication

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLightningOpen-Source ToolsCloud Computing Platforms

Industry Keywords

Applied ResearchMachine LearningNatural Language ProcessingAI DevelopmentModel Sparsification

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
Use 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 that advances AI developments into next-generation customer experiences
Translate complex research and technical work into tangible business goals
Collaborate with senior researchers on internal technical reports and 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, with the degree obtained by the scheduled start date; or an M.S. in these fields plus 2 years of experience in Applied Research
Deep understanding 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, 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 degree with 5 years of industrial NLP research experience
Preferred: Publications related to pre-training large language models, deep learning theory, or listed AI conferences
Preferred: Experience training a large language model from scratch with 10B+ parameters and 500B+ tokens
Preferred: Experience with model sparsification, quantization, training parallelism, gradient checkpointing, or model compression
Preferred: Experience optimizing training for a 10B+ model
Preferred: Deep knowledge of deep learning algorithms or optimizer design
Preferred: Experience with compiler design
Preferred: Experience with supervised fine-tuning, instruction-tuning, dialogue-finetuning, or parameter tuning
Preferred: Knowledge of transfer learning, model adaptation, and model guidance
Preferred: Experience deploying a fine-tuned large language model
Preferred: Ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks
Preferred: Experience designing controlled experiments and documenting reproducibility results

Benefits

Comp & perks

Performance-based incentive compensation, which may include cash bonuses 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