Senior AI Foundations Researcher (LLMs & Models)

Capital One; San Jose (CA); On-site; USD 334,000 - 381,000; Full time

Benefits offered by this job

Performance-based incentives

Job summary

Capital One is seeking an AI Foundation Models lead to advance scalable AI for customer experiences. You will partner with data scientists, software engineers, and product managers to develop and deploy foundation models across domains.

You will work with PyTorch, AWS Ultraclusters, HuggingFace, and VectorDBs, drive research, and translate complex research into business outcomes. This role requires a PhD/MS with extensive applied research and a track record of publications.

Qualifications

• PhD or MS with extensive applied research experience in AI/ML.
• Experience building large deep learning models and LLMs.
• Strong publication record and ability to lead research direction.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Build AI foundation models through all development phases.
• Engage in high impact applied research to advance customer experiences.
• Leverage PyTorch, AWS Ultraclusters, HuggingFace, Lightning, VectorDBs to analyze data.
• Translate complex work into tangible business goals.

Skills

Open-source languages

LLM development

Model training optimization

Publications in ML/NLP venues

Education

PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields

MS in Electrical/Computer Engineering, CS, AI, Mathematics with 6+ years applied research

Tools

Pytorch

AWS Ultraclusters

HuggingFace

Lightning

VectorDBs

Job description

Capital One is seeking an AI Foundation Models lead to advance scalable AI for customer experiences. You will partner with data scientists, software engineers, and product managers to develop and deploy foundation models across domains.

You will work with PyTorch, AWS Ultraclusters, HuggingFace, and VectorDBs, drive research, and translate complex research into business outcomes. This role requires a PhD/MS with extensive applied research and a track record of publications.