Our exciting internship opportunities for this Summer 2024 are now available. We are looking for students pursuing advanced degrees in Computer Science and Electrical Engineering. Internships are typically 3 months long in duration. The benefits of working for us include the opportunity to quickly become part of a project team applying cutting-edge technology to industry-leading concepts. We have opportunities in Data Science & System Security, Integrated Systems, Media Analytics, Machine Learning, and Optical Networking & Sensing.

Visit our Internship page to learn more about our programs, our Careers page for all of our employment opportunities and apply below for your internship by department and location. Good luck!

Summer Intern 2024
Position Department Location Currently Accepting Applications
DSSS – Research Intern Data Science and System Security Princeton, New Jersey Yes
IS – Research Intern Integrated Systems Princeton, New Jersey No
MA – Research Intern Media Analytics San Jose, California No
ML – Research Intern Machine Learning Princeton, New Jersey Yes
ONS – Research Intern Optical Networking and Sensing Princeton, New Jersey No

Read Our News Posts

Summer 2025 Intern SMM

Apply for a Summer 2025 Internship

Our exciting internship opportunities for this Summer 2025 are now available. We are looking for students pursuing advanced degrees in Computer Science and Electrical Engineering. Internships are typically 3 months long in duration. The benefits of working for us include the opportunity to quickly become part of a project team applying cutting-edge technology to industry-leading concepts. We have opportunities in Data Science & System Security, Integrated Systems, Media Analytics, Machine Learning, and Optical Networking & Sensing.
Princeton Interns 2024

Summer Interns 2024

Learn about the amazing group of interns who joined us at Princeton and San Jose campuses this summer. Their hard work, fresh perspectives, and dedication have truly made an impact across the board, from cutting-edge research projects to innovative software development initiatives.
Introducing the Trustworthy Generative AI Project Pioneering the Future of Compositional Generation and Reasoning Blog Post

Introducing the Trustworthy Generative AI Project: Pioneering the Future of Compositional Generation and Reasoning

We are thrilled to announce the launch of our latest research initiative, the Trustworthy Generative AI Project. This ambitious project is set to revolutionize how we interact with multimodal content by developing cutting-edge generative models capable of compositional generation and reasoning across text, images, reports, and even 3D videos.
Introducing Our New Project Time Series Language Model for Explainable AI Blog Post

Introducing Our New Project: Time Series Language Model for Explainable AI

Our new project, Time Series Language Model for Explainable AI, represents a significant leap forward in the field of forecasting and explainable AI. By combining advanced forecasting techniques with explainable AI, we are paving the way for a future where data-driven insights are not only accurate but also comprehensible and actionable.
Agentic LLMs for AI Orchestration Project Revolutionizing Complex Workflows

Agentic LLMs for AI Orchestration Project: Revolutionizing Complex Workflows

The development of Agentic LLMs for AI Orchestration represents a significant advancement in artificial intelligence. By seamlessly integrating computer vision, logic, and compute modules, our LLM is poised to revolutionize the way complex workflows are managed and executed. Supported by robust research and driven by innovative training methodologies, our agentic LLM sets a new standard in AI orchestration, offering unparalleled performance and adaptability.
The Evolution of Disciplines From Experimental Roots to Theoretical Frameworks Blog Post

The Evolution of Disciplines: From Experimental Roots to Theoretical Frameworks

Chris White discusses the evolution of scientific disciplines, which often begin with exploration driven by curiosity and experimentation. As fields grow in complexity and cost, they shift to theoretical frameworks that optimize research. This transition is crucial for sustainable progress. Currently, AI and ML remain largely experimental, highlighting the need for theoretical foundations to ensure development.