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Capital One
Capital One
H1B Visa SponsorBankingFinanceFintech
Capital One is a financial services and fintech company offering credit cards, auto loans, banking, and savings products. Its work combines financial expertise with technology and digital tools to improve how customers manage money. The company’s careers focus includes building customer-oriented solutions within a diverse and inclusive workforce.
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Applied Researcher 4, AI Foundations and Multimodal Guardrails

Advance multimodal guardrails and AI foundation models for Capital One’s banking experiences. Lead research from experimentation through production implementation.

USUnited StatesCACaliforniaMAMassachusettsNYNew YorkVAVirginia
$218,700 – $272,300 / year
On-siteFull-timeJuniorMiddleEnglish RequiredArtificial Intelligence
AWSCloudPyTorch

Description

  • Collaborate with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
  • Apply PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and related technologies to analyze large-scale numeric and textual data
  • Design, train, evaluate, validate, and implement AI foundation models
  • Perform applied research that advances AI capabilities for next-generation customer experiences
  • Convert complex research and technical work into measurable business objectives
  • Work with senior researchers on technical reports and conference submissions covering novel methods and findings

Requirements

  • Pursuing or holding a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field by the scheduled start date; alternatively, an M.S. in one of these fields with 2 years of Applied Research experience
  • Strong command of AI methodologies
  • Experience developing large deep learning models for language, images, events, or graphs
  • Expertise in at least one of training optimization, self-supervised learning, robustness, explainability, or RLHF
  • Demonstrated ability to deliver models at scale across training data and inference workloads
  • Experience contributing libraries, platform code, or solution code to existing products
  • Record of high-quality machine learning contributions, including first-author publications or comparable projects
  • Ability to define and pursue a research agenda while independently managing long-term projects
  • Practical experience building AI foundation models and solutions with open-source tools and cloud platforms
  • Preferred: PhD in a related technical discipline
  • Preferred: PhD focus in NLP for LLMs or a master’s degree plus 5 years of industrial NLP research experience
  • Preferred: Publications on large language model pre-training, deep learning theory, or recognized AI conferences
  • Preferred: Experience training a large language model from scratch with more than 10B parameters and 500B tokens
  • Preferred: Experience with model sparsification, quantization, training parallelism, gradient checkpointing, or model compression
  • Preferred: Experience optimizing training for models exceeding 10B parameters
  • Preferred: Advanced knowledge of deep learning algorithms or optimizer design
  • Preferred: Experience with compiler design
  • Preferred: Experience with supervised fine-tuning, instruction tuning, dialogue fine-tuning, or parameter tuning
  • Preferred: Knowledge of transfer learning, model adaptation, and model guidance
  • Preferred: Experience deploying fine-tuned large language models
  • Preferred: Ability to reproduce and extend peer-reviewed AI research with modern open-source frameworks
  • Preferred: Experience designing controlled experiments and documenting reproducibility results

Benefits

  • Performance-based incentive compensation may include cash bonuses and/or long-term incentives
  • Broad, competitive, and inclusive health, financial, and other benefits designed to support overall well-being
  • Employment authorization sponsorship may be considered for a newly qualified applicant

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