Current PhD, AI Engineering Internship Program - Summer 2027

About the role

This is a full-time paid internship program spanning twelve weeks from June through August. Participation in the internship requires that you are located in the continental United States with in-person attendance at your assigned location, in accordance with Capital One’s hybrid working model, for the duration of the program. Interns will be evaluated for a full-time position with their team and will work with their manager on identifying a start date upon graduation.

Responsibilities

• Partner deeply with a cross-functional team of research scientists, PMs, and engineers to prototype and ship AI-native products that reach millions of customers.
• Research, prototype, and productionalize high-impact AI systems, including multimodal search, intelligent document processing, and autonomous agentic workflows that push the boundaries of current industry benchmarks.
• Design and optimize the critical infrastructure of our AI stack—from fine-tuning pre-training pipelines and reinforcement learning to implementing inference optimization, robust guardrails and sophisticated evaluation frameworks.
• Leverage a broad stack of technologies including AWS Ultraclusters, PyTorch, and leading-edge agentic frameworks.
• Architect agentic workflows that go beyond simple chat—enabling AI systems to autonomously navigate tools, orchestrate multi-step reasoning, and integrate seamlessly with complex microservice environments.

Requirements

• Currently has, or is in the process of obtaining a PhD in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, with an expectation that the required degree will be obtained by August 2029 or earlier.
• Must be continuing in the same course of study of the most recent degree following completion of the internship period.
• At least 1 year of experience or academic work developing AI and ML algorithms or technologies.
• At least 1 year of experience or academic work programming with Python, Go, Scala, or Java.

Preferred Qualifications

• Experience or academic work with deploying AI/ML systems on cloud platforms (e.g., AWS, Google Cloud, Azure).
• Experience or academic work in developing and applying state-of-the-art techniques for optimizing AI/ML training or inference pipelines, including distributed GPU computational frameworks.
• Experience or academic work with AI/ML domains and systems (e.g., LLM Inference, Search and Retrieval, NLP, Computer Vision, Guardrails, Memory).
• Familiarity with Agentic Frameworks (Eg: LangChain, LangGraph, LlamaIndex, Autogen, MCP/A2A, frontier-labs agent SDKs).

Qualifications

• Basic Qualifications: See above.
• Preferred Qualifications: See above.

Skills

• Strong foundation in engineering and mathematics.
• Expertise in hardware, software, and AI.
• Ability to decompose complex problems.
• Judgment to decide where AI adds value and how to orchestrate AI workflows incorporating time-tested systems design principles, integrating both into a unified whole.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website.

Pay

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

• McLean, VA: $176,000 - $176,000 for AI Engineer PhD Intern
• New York, NY: $192,000 - $192,000 for AI Engineer PhD Intern
• San Jose, CA: $192,000 - $192,000 for AI Engineer PhD Intern

Schedule

This is a full-time paid internship program spanning twelve weeks from June through August. Participation in the internship requires that you are located in the continental United States with in-person attendance at your assigned location, in accordance with Capital One’s hybrid working model, for the duration of the program.

Qualifications

• Basic Qualifications: See above.
• Preferred Qualifications: See above.

Skills

• Strong foundation in engineering and mathematics.
• Expertise in hardware, software, and AI.
• Ability to decompose complex problems.
• Judgment to decide where AI adds value and how to orchestrate AI workflows incorporating time-tested systems design principles, integrating both into a unified whole.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website.

Pay

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

• McLean, VA: $176,000 - $176,000 for AI Engineer PhD Intern
• New York, NY: $192,000 - $192,000 for AI Engineer PhD Intern
• San Jose, CA: $192,000 - $192,000 for AI Engineer PhD Intern