AI Foundations Researcher I

AIToolboard; McLean (VA); On-site; USD 120,000 - 190,000; Full time

Job summary

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

Qualifications

• 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.

Responsibilities

• 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.

Skills

Analytical thinking

Open-source

Cloud computing

Leadership

Education

PhD in CS, EE, CE, AI or related

MS + 2 years Applied Research

Tools

PyTorch

AWS Ultraclusters

Huggingface

VectorDBs

Job description

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