Research Intern - Cloud Competitive Intelligence
Microsoft | |
United States, California, Mountain View | |
Dec 21, 2024 | |
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.The Strategic Planning and Architecture (SPARC) group conducts cloud competitive landscape and technology analysis to help us understand potential directions that cloud completion is taking and assess Azure's competitive gaps. As a Research Intern in the SPARC group your work will involve reading technical papers, blogs, market and competitive analysis reports and building analytical frameworks.
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 ResponsibilitiesEvaluate AI/ML large language models and help build an understanding of the relationship between model sizes and the size of GPU/accelerator clusters that are needed to train and infer these models.Help build a view of the long-term growth of AI large language models and how they would deploy on future GPU accelerator clusters that are built by AI vendors and large hyperscalers.Develop performance, cost analysis, and modelling perspectives for future AI GPUs. |