Building the future: highlights from Dropbox’s 2025 summer intern class
Dropbox’s 2025 intern program brought together 43 interns from 27 universities for 12 weeks of mentorship, technical work, and community-building. The 28 engineering interns contributed to systems spanning AI, search, storage, data infrastructure, and developer tools, with many projects supporting Dropbox Dash. Their work demonstrates how targeted refactoring, automation, and intelligent infrastructure can improve reliability, reduce costs, and expand product capabilities. ## A Diverse, Mentorship-Focused Internship Program - Interns received more than 6,000 hours of one-on-one mentorship. - The cohort included students from institutions in the United States, Canada, Poland, and Ireland. - Programming included Virtual First events, employee resource group activities, and an in-person Emerging Talent Summit. - Projects were aligned with Dropbox’s production systems and company goals rather than being isolated experiments. ## Infrastructure and Reliability Improvements - **Filesystem Data:** Rhea Rai redesigned Dropbox’s file history tracking system, emphasizing strongly tested code and simpler metadata infrastructure while reducing operational costs. - **Storage Core:** Albert Joon Sung reduced Magic Pocket write latency during disk restarts by adding storage-health caching and routing writes away from degraded volumes. - **Metrics:** Yonatan Ginsburg developed adaptive anomaly detection for Vortex2, accounting for changing patterns and seasonality to reduce alert fatigue and improve incident response. - **Analytics Platform:** Sanjith Udupa built recommendations for optimizing Databricks queries and ETL pipelines, and documented a plan to migrate a 500 TB mobile-events dataset to liquid clustering. ## AI, Search, and Dropbox Dash - **ML Platform:** Ben Juntilla created AI Sentinel, which gives engineers real-time visibility into machine-learning deployment health and improves confidence in model releases. - **Connector Platform:** Eddie Ormseth built tools that provide access to fresher Dash persistence data and additional third-party metadata without requiring connector teams to reprocess data. - **Retrieval Platform:** Rishi Peddakama expanded unified search to more than 20 languages by integrating language detection into indexing and retrieval. - **Find & Discover:** Francesca Venditti created in-context document previews for Dash, including PDF viewing and links to AI-powered follow-up chat. - **Conversational AI:** Alan Zhu developed a modular web-automation agent and connected it to Dropbox APIs for actions such as searching for and uploading files. ## Developer Automation - Ahmed Ibrahim built an AI-assisted code migration tool on Dropbox’s internal migration platform. - Developers can run migrations on selected folders, configure them through a CLI or automated workflow, and receive pull requests automatically when jobs succeed. - The tool enabled two major migrations during the internship and illustrates how automation can reduce repetitive engineering work. ## Broader Impact The interns’ projects improved system performance, operational visibility, multilingual accessibility, data freshness, and developer productivity. Together, they supported Dropbox’s move toward AI-first products while reinforcing the company’s emphasis on trustworthy, maintainable, and efficient engineering. For students interested in production-scale software, AI, and infrastructure, Dropbox presents its internship program and open roles as opportunities to contribute directly to products such as Dropbox Dash.
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