AI Foundations Researcher I

AIToolboard

McLean (VA)

Presencial

USD 120.000 - 190.000

Jornada completa

14 días+

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Descripción de la vacante

Capital One is seeking an Applied Researcher I (AI Foundations) to join our AI Foundations team. The role focuses on building trustworthy AI systems and delivering AI-powered customer experiences in collaboration with data scientists, software engineers, ML engineers and product managers.

You will work with PyTorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more to develop foundation models, train and evaluate them, and translate research into scalable production capabilities

Formación

  • Currently pursuing or has a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics or related field, with degree by start date or MS with 2 years applied research experience.
  • Experience with large language models, NLP or ML research preferred.
  • Strong publication record or project contributions in ML.

Responsabilidades

  • Collaborate with a cross-functional team of data scientists, software engineers, ML engineers and product managers to deliver AI-powered products.
  • Develop AI foundation models from design through training, evaluation, validation and deployment.
  • Translate research outcomes into scalable, customer-facing features.
  • Engage in applied research to push AI developments into production systems.
  • Communicate technical concepts to non-technical stakeholders.

Conocimientos

Analytical thinking
Open-source
Cloud computing
Leadership

Educación

PhD in CS, EE, CE, AI or related
MS + 2 years Applied Research

Herramientas

PyTorch
AWS Ultraclusters
Huggingface
VectorDBs

Descripción del empleo

Capital One is seeking an Applied Researcher I (AI Foundations) to join our AI Foundations team. The role focuses on building trustworthy AI systems and delivering AI-powered customer experiences in collaboration with data scientists, software engineers, ML engineers and product managers.

You will work with PyTorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more to develop foundation models, train and evaluate them, and translate research into scalable production capabilities

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