C

Capital One

Issues credit cards and runs a consumer bank

Applied Researcher 5

Natural Language Processing & LLMsConfirmed 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, Artificial Intelligence, Mathematics, or a related field, with two years of experience in Applied Research; alternatively, an M.S. in Electrical Engineering, Computer Engineering, Computer Science, Artificial Intelligence, Mathematics, or a related field plus four years of experience in Applied Research.
  • 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 one or more of training optimization, self-supervised learning, robustness, explainability, or RLHF.
  • 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 machine learning ideas or improving existing ideas, demonstrated by accomplishments such as first-author publications or projects.
  • Can own and pursue a research agenda, choose impactful research problems, and independently carry out long-running projects.
  • Has hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Has experience building large language models from scratch as a member of a team, at 10 billion or more parameters and 500 billion or more tokens.
  • Has multiple publications on large language model pre-training topics, such as technical reports of pre-trained LLMs, self-supervised learning techniques, or model pre-training optimization.
  • Has publications in deep learning theory or at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.
  • Has multiple years of experience and/or publications in model sparsification, quantization, training parallelism or partitioning design, gradient checkpointing, or model compression.
  • Has experience optimizing training for a 10-billion-or-larger model and deep knowledge of deep learning algorithmic or optimizer design.
  • Has experience with compiler design.
  • Has demonstrated knowledge of transfer learning, model adaptation, and model guidance principles.
  • Has experience deploying a fine-tuned large language model.

Responsibilities

  • Partners with 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 identify insights in large volumes of numeric and textual data.
  • Builds AI foundation models through design, training, evaluation, validation, and implementation.
  • Conducts applied research to translate recent AI developments into customer experiences.
  • Translates complex technical work into tangible business goals.
  • Leads cross-functional research threads linking prototype model development and deployment with machine learning engineering partners, ensuring research translates into production impact.
  • Researches and evaluates emerging technologies, stays current on state-of-the-art methods, technologies, and applications, and identifies opportunities to apply them.
  • Works with stakeholders to identify and improve existing practices.

Desired Qualifications

  • Preferred: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field.
  • For LLM research: PhD focused on natural language processing, or a master's degree with five years of industrial NLP research experience.
  • For optimization of training and inference: PhD focused on optimizing training of very large deep learning models.
  • For fine-tuning: PhD focused on guiding LLMs with further tasks such as supervised fine-tuning, instruction tuning, dialogue fine-tuning, or parameter tuning.

About the Company

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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