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, AI, Mathematics, or a related field, with two years of experience in Applied Research; alternatively, an M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field plus four years of experience in Applied Research.
  • 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 generating high-quality machine learning ideas or improving existing ideas, demonstrated through 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 deep understanding of the foundations of artificial intelligence methodologies.
  • Has hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Has a PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field, as a preferred qualification.
  • For the LLM specialization, has a PhD focus in natural language processing or a master's degree with five years of industrial natural language processing research experience; has multiple publications on large language model pre-training topics; has been a member of a team that trained a large language model from scratch with at least 10 billion parameters and 500 billion tokens; has publications in deep learning theory and at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.
  • For training and inference optimization, has a PhD focused on optimizing training of very large deep learning models; 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-plus-parameter model; has deep knowledge of deep learning algorithms and/or optimizer design; and has compiler design experience.
  • For fine-tuning, has a PhD focused on guiding large language models 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.

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 derive insights from large volumes of numeric and textual data.
  • Builds AI foundation models through design, training, evaluation, validation, and implementation.
  • Conducts applied research to bring recent AI developments into future customer experiences.
  • Translates complex research into tangible business goals.
  • Leads cross-functional research threads that bridge prototype model development and deployment with machine learning engineering partners, ensuring research insights translate 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 approaches.

Desired Qualifications

  • For the LLM specialization, has a PhD focus in natural language processing or a master's degree with five years of industrial natural language processing research experience; has multiple publications on large language model pre-training topics; has been a member of a team that trained a large language model from scratch with at least 10 billion parameters and 500 billion tokens; has publications in deep learning theory and at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.
  • For training and inference optimization, has a PhD focused on optimizing training of very large deep learning models; 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-plus-parameter model; has deep knowledge of deep learning algorithms and/or optimizer design; and has compiler design experience.
  • For fine-tuning, has a PhD focused on guiding large language models 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.

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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