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Capital One

Issues credit cards and runs a consumer bank

Applied Researcher 4 - AI Foundations, Graph and Behavioral Models

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Currently has or is in the process of obtaining a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field, with the degree obtained on or before the scheduled start date; alternatively, has an M.S. in one of those fields plus two years of applied research experience.
  • Has 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.
  • Has experience building large deep learning models for language, images, events, or graphs, and expertise in at least one of training optimization, self-supervised learning, robustness, explainability, or reinforcement learning from human feedback.
  • Has a track record of delivering models at scale in terms of training data and inference volumes.
  • Has experience delivering libraries, platform-level code, or solution-level code to existing products.
  • Has a track record of producing high-quality ideas or improving existing machine learning ideas, demonstrated by accomplishments such as first-author publications or projects.
  • Can own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.
  • Has a PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field (preferred).
  • For LLM-focused work, has a PhD focused on natural language processing or a master's degree plus five years of industrial NLP research experience; has multiple publications on pretraining large language models; has been part of a team that trained a large language model from scratch with 10B+ parameters and 500B+ tokens; has publications in deep learning theory; and has publications at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.
  • For behavioral-model work, has a PhD focused on geometric deep learning topics such as graph neural networks, sequential models, or multivariate time series; has multiple papers on training models on graph and sequential data structures at KDD, ICML, NeurIPS, or ICLR; has scaled graph models to more than 50 million nodes; has experience with large-scale deep-learning-based recommender systems and production real-time and streaming environments; has contributed to open-source frameworks such as PyTorch Geometric or DGL; has proposed methods for inference or representation learning on graphs or sequences; and has worked with datasets containing more than 100 million users.
  • For fine-tuning work, has a PhD focused on guiding LLMs with further tasks such as supervised fine-tuning, instruction tuning, dialogue fine-tuning, or parameter tuning; demonstrates knowledge of transfer learning, model adaptation, and model guidance; and has experience deploying a fine-tuned large language model.
  • For data preparation work, has publications studying tokenization, data quality, dataset curation, or labeling; has contributed to a major open-source corpus; or has contributed to open-source libraries for data quality, dataset curation, or labeling.
  • Can reproduce and extend peer-reviewed AI research using modern open-source frameworks.
  • Has experience designing controlled experiments and documenting reproducibility results for internal or public research.

Responsibilities

  • Partners with a cross-functional team of data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
  • Uses technologies including PyTorch, AWS Ultraclusters, Hugging Face, and Lightning to analyze large volumes of numeric and textual data.
  • Builds AI foundation models through design, training, evaluation, validation, and implementation.
  • Conducts applied research to advance AI developments into customer experiences.
  • Translates complex work into tangible business goals.
  • Collaborates with senior researchers to prepare internal technical reports or conference submissions summarizing novel methods or findings.
  • Researches and evaluates emerging technologies, stays current on published state-of-the-art methods, technologies, and applications, and identifies opportunities to apply them.
  • Works with stakeholders to identify and improve the status quo.

Desired Qualifications

  • Demonstrated a focus on AI through a PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field.
  • For LLM-focused work, multiple publications on LLM pretraining topics, membership on a team that trained an LLM from scratch with 10B+ parameters and 500B+ tokens, publications in deep learning theory, and publications at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.
  • For behavioral-model work, specialization in geometric deep learning, including graph neural networks, sequential models, or multivariate time series; publications on graph and sequential data structures; experience scaling graph models beyond 50 million nodes and with large-scale recommenders, real-time and streaming production environments, open-source framework contributions, new methods for graph or sequence inference or representation learning, and datasets exceeding 100 million users.
  • For fine-tuning work, a PhD focus on guiding LLMs through additional tasks, knowledge of transfer learning, model adaptation, and model guidance, and experience deploying a fine-tuned LLM.
  • For data preparation work, publications or open-source contributions related to tokenization, data quality, dataset curation, labeling, or major corpora.
  • Ability to reproduce and extend peer-reviewed AI research with modern open-source frameworks.
  • Experience designing controlled experiments and documenting reproducibility results for internal or public research.

About the Company

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Capital One

Issues credit cards and runs a consumer bank

Capital One runs a consumer and commercial bank that issues credit cards, takes deposits, and finances cars and businesses. Its Venture travel cards and Quicksilver cash-back cards let customers earn rewards on everyday spending, while its online banking tools manage payments and savings. Customers use checking and savings accounts through an app, branches, and cash machines, and commercial clients use treasury tools to manage company cash. The bank earns interest on loans and fees from banking and card transactions, with customer deposits helping fund its lending operations. Capital One was founded in 1994 and has its headquarters in McLean, Virginia.

Company size
10,001+
Company stage
IPO
Headquarters
McLean, VA
Founded
1994

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