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Capital One
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October 24, 2025
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Applied Researcher I

San Jose, CA
Full-time
Onsite
$214K/yr - $245K/yr
Entry Level
Capital One is a leading financial services company focused on creating trustworthy and reliable AI systems for banking. The Applied Researcher I role involves collaborating with cross-functional teams to deliver AI-powered products and conducting applied research to enhance customer experiences using cutting-edge AI methodologies.
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Responsibilities

  • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
  • Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
  • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
  • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Qualification

Required

  • Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research
  • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Has a deep understanding of the foundations of AI methodologies.
  • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
  • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
  • Experience in delivering libraries, platform level code or solution level code to existing products.
  • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
  • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Preferred

  • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
  • LLM
  • PhD focus on NLP or Masters with 5 years of industrial NLP research experience
  • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)
  • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)
  • Publications in deep learning theory
  • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
  • PhD focused on topics related to optimizing training of very large deep learning models
  • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression
  • Experience optimizing training for a 10B+ model
  • Deep knowledge of deep learning algorithmic and/or optimizer design
  • Experience with compiler design
  • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
  • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
  • Experience deploying a fine-tuned large language model

Benefit

  • Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Capital One is a financial services company that provides banking, credit card, auto loan, savings, and commercial banking services.
Glassdoor
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Founded in 1994
Mclean, Virginia, USA
10001+ employees
http://www.capitalone.com