Research Intern - Agentic Data Memory

Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. Research Interns work on well-defined projects that encourage open exploration and collaboration, guided by dedicated mentors. Currently enrolled in a Doctorate Degree program in Computer Science or a related STEM field. In addition to the qualifications below, you'll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter. 1+ year(s) of research experience in natural language processing, information retrieval, machine learning, graph machine learning, or systems for AI, demonstrated through publications or preprints. Experience building or evaluating LLM-based agents, retrieval-augmented generation (RAG), knowledge graphs, or memory systems for agents is strongly preferred. Experience designing benchmarks, evaluation protocols, or controlled experiments, including statistical analysis of results, is a significant plus. 1+ year(s) experience in Python and domain-relevant libraries and frameworks (e.g., PyTorch); familiarity with running experiments on GPU clusters or cloud infrastructure is a plus. 1+ year(s) experience in Calculus, Probability and Statistics and/or Machine Learning.