Current PhD, AI Engineering Internship Program - Summer 2027
$176k - $176k • New York, NY • Internship
Posted 1mo ago
About the job
This is a full-time paid internship program spanning twelve weeks from June through August, requiring in-person attendance at the assigned location in New York, NY, in accordance with Capital One’s hybrid working model. Interns will be evaluated for a full-time position upon graduation. The program focuses on building industry-leading agentic capabilities and scalable, high-performance AI infrastructure, contributing to AI-native experiences and products for over 100 million customers. You will work on the Intelligent Foundations and Experiences (IFX) team, advancing the state-of-the-art in AI science and engineering.
Responsibilities
- Partner with research scientists, PMs, and engineers to prototype and ship AI-native products.
- Research, prototype, and productionalize high-impact AI systems, including multimodal search, intelligent document processing, and autonomous agentic workflows.
- Design and optimize AI stack infrastructure, including fine-tuning pre-training pipelines, reinforcement learning, inference optimization, guardrails, and evaluation frameworks.
- Leverage technologies like AWS Ultraclusters, PyTorch, and agentic frameworks.
- Architect agentic workflows that enable AI systems to autonomously navigate tools, orchestrate multi-step reasoning, and integrate with microservice environments.
Requirements
- Currently pursuing a PhD in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, with expected completion by August 2029 or earlier.
- Must continue in the same course of study after the internship.
- 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.
- Experience or academic work deploying AI/ML systems on cloud platforms (e.g., AWS, Google Cloud, Azure).
- Experience or academic work in developing and applying 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 (e.g., LangChain, LangGraph, LlamaIndex, Autogen, MCP/A2A, frontier-labs agent SDKs).
Benefits
- Paid internship program
- Evaluation for a full-time position upon graduation
- Access to top-tier developer tools like Claude Code and Windsurf