The Walt Disney Company is seeking a Storage Analytics Intern for Summer 2026 to join their dedicated Storage and Backup team. This role involves enhancing creative workflows by pioneering a generative AI chatbot that allows artists to interact with data in natural language, while also working on large-scale infrastructure and innovative solutions.
Design and implement a working prototype of a large language model (LLM)-backed chatbot, focusing on a user experience that resonates with a creative pipeline
The bot should intuitively answer artistic and project-based queries, bridging the gap between technical storage metrics and creative needs
Help engineer efficient pipelines to extract, structure, and tag the essential technical and descriptive metadata embedded within our media files (resolution, color space, project tags, versioning details)
Leverage our existing high-performance computing infrastructure and analytics tools to process massive datasets
Qualification
Required
Excellent scripting language skills, including Python & Shell
Experience with Generative AI frameworks (e.g., LangChain, OpenAI API, Hugging Face) and Large Language Models (LLMs)
Understanding of data structures, metadata extraction, or database querying (SQL/NoSQL)
Ability to translate complex technical data into intuitive insights for digital artists and technical creatives
Minimally a junior in college working towards a degree or certificate in computer science, computer graphics, or other area of relevant study
Recent graduates who are within the first year after graduation are eligible to apply
You already possess the legal right to work in the United States
This is a full-time position. You must be available to work on-site Mon 6.1.26 - Fri 8.21.26
Preferred
Familiarity with Linux/Unix environments
Knowledge of file systems or cloud storage fundamentals
Interest in film, animation, VFX, or digital content creation pipelines
Benefits
The Walt Disney Company started as a cartoon studio and evolves into sports coverage and television shows.