Research Intern - Memory & Orchestration in Large Language Models
 Microsoft | |
 United States, Washington, Redmond | |
 Jan 03, 2025 | |
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OverviewResearch Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. Our Societal Resilience team is seeking Research Interns to join us in pushing the boundaries of AI capabilities with large language models (LLMs) and multimodal models. Our mission is to prepare for the unknown challenges of the future by developing resilient systems and technologies that can support societal and individual resilience during times of crisis. The research focuses on memory and orchestration within LLMs and multimodal models. We are particularly interested in developing new methods for leveraging and training various types of embeddings, such as graph embeddings and multimodal embeddings, creating advanced retrieval augmented generation (RAG) systems, and conducting specialized context-specific fine-tuning to build more capable and adaptive models. We believe that these capabilities will play a critical role in building resilience by amplifying the ability of individuals and organizations to respond to uncertainty.
ResponsibilitiesResearch 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.Additional ResponsibilitiesConducting hands-on research into systems for memory and orchestration of LLMs and multimodal models. Investigating new embedding techniques, including graph embeddings and multimodal embeddings. Developing advanced retrieval augmented generation systems to enhance LLM capabilities. Specializing in context-specific fine-tuning for creating adaptable AI systems. Collaborating with interdisciplinary teams of researchers and engineers on challenging and impactful projects. Presenting research findings and participating in research discussions. | |