Summer PhD Applied AI Research Internship

Capital One; McLean (VA); Hybrid; USD 172,000 - 210,000; Full time

Job summary

Capital One is offering a twelve-week, summer Applied Research Internship for PhD students in the continental United States, with in-person attendance at assigned locations under a hybrid model. This paid program does not sponsor employment authorization for the internship, but may lead to a full-time Applied Research role with sponsorship eligibility.

The role emphasizes research in AI/ML with exposure to industry-scale challenges, collaboration with cross-functional teams, and opportunities to

Qualifications

• Currently enrolled in an accredited PhD program.
• 1st year of PhD coursework must be completed by June 2027.

Responsibilities

• Join Capital One for a full-time, 12 week, summer applied research experience.
• Engage in high impact applied research with the goal of taking the latest AI developments and pushing them into the next generation of customer experiences or publications.
• Partner with a cross-functional team to test and design AI-powered products that transform how customers interact with their money.
• Leverage technologies such as PyTorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs to extract insights from large data sets.
• Translate complex work into tangible business goals.
• Collaborate with leading researchers to publish papers at top conferences.
• Participate in networking sessions, technical deep dives and executive speaker sessions.

Skills

Python

PyTorch

Publications

PhD required

Education

PhD in CS/related

Tools

AWS Ultraclusters

Huggingface

Lightning

VectorDBs

Job description

Capital One is offering a twelve-week, summer Applied Research Internship for PhD students in the continental United States, with in-person attendance at assigned locations under a hybrid model. This paid program does not sponsor employment authorization for the internship, but may lead to a full-time Applied Research role with sponsorship eligibility.

The role emphasizes research in AI/ML with exposure to industry-scale challenges, collaboration with cross-functional teams, and opportunities to