Summer 2027: AI Scientist Intern

Role overview Contribute to the development and evaluation of AI systems for digital learning products. This summer internship combines applied machine learning, data preparation, and model analysis, with a focus on potential uses such as personalized learning and content recommendations and on communicating technical findings to partner teams.

Responsibilities - Support the development, testing, and evaluation of machine learning models. - Explore where AI methods could help personalize learning, recommend content, or inform student outcomes. - Prepare data through collection, cleaning, and feature engineering, and assist with model validation. - Analyze model outputs to identify patterns, anomalies, and opportunities to improve performance. - Document methods and results in technical reports, performance analyses, or research presentations. - Join product demonstrations and discussions with data science and product colleagues to understand how AI features are used.

Requirements - Be enrolled in an undergraduate or graduate degree program and plan to return to school in fall 2027. - Be available full time from June 7 through August 13, 2027, and authorized to work and reside in the United States during the internship. - Communicate clearly and synthesize information into themes and findings. - Have an interest in K–12 education technology and applying data-informed approaches to learning.

Nice to have - Familiarity with natural language processing, large language models, or generative AI. - Experience with data analysis, statistical modeling, or AI and machine learning research through coursework or projects. - Interest in responsible AI, AI ethics, adaptive learning, or personalization. - Familiarity with Python, R, or SQL; cloud platforms, version control, research tools, or data visualization are useful.

Benefits and work setup The 10-week internship is paid and remote, with a two-day in-person gathering in Brooklyn. It includes mentorship, hands-on training, product demonstrations, a speaker series, and exposure to machine learning, language technologies, adaptive learning, and responsible AI.