We are a team at Microsoft Research that spans both the General Artificial Intelligence group (formerly Natural Language Computing group) and Microsoft Research Asia – Vancouver lab, focusing on Multimodal AI research. We work on innovative research projects and exciting challenges in multimodal foundation models, generative AI techniques, document intelligence, and more. Our team has contributed influential open-sourced research that advances the multimodal capabilities in Large Foundation Models and General AI. These contributions have also been widely applied to Microsoft products and services.

We are seeking talented and motivated research interns to join us in cutting-edge Multimodal AI research. As a research intern, you will develop generalizable technologies that enhance the multimodal capabilities of AI models. You will collaborate with a pioneering team of world-class researchers across our Vancouver, Beijing, and Redmond labs to push for real-world applications. Ideal candidates will have a background in Computer Vision, Natural Language Processing, Machine Learning, and/or Document Understanding. We value your ideas and unique viewpoints and believe that our partnership will shape ambitious and impactful research contributions.

Join our pioneering research team to work on harnessing the power of Large Language Models (LLMs) to address complex real-world optimization problems requiring long-term planning and dynamic information gathering from environments. Traditional optimization techniques often struggle with the high dimensionality, dynamic nature, and intricate dependencies inherent in real-world settings. 

Addressing these challenges, our research aims to push the boundaries of LLM capabilities to automate the decision-making processes, improve reliability, and provide innovative solutions to both existing and classical optimization challenges. The successful candidate will have the opportunity to collaborate with world-class researchers and engineers from diverse backgrounds and expertise, access to state-of-the-art computational resources, and contribute to the advancement of LLM research and its impact on real-world optimization problems.

Knowledge is essential for identifying issues, accelerating remediation, and enhancing existing infrastructure in large-scale systems. However, there is a knowledge gap due to the lack of easily consumable, vast infrastructure data. Because the data is immense and dynamically evolving. Large-language and multi-modal models have created opportunities to better support knowledge production and consumption, from gleaning new insights to extracting entities and generating signatures from unstructured data at scale, as demonstrated in recent research. In this project, we aim to leverage these models to automate and accelerate raw data processing, build knowledge graphs, and connect them to gain a deeper understanding of system infrastructure.

We’ll work with scientists who are at the forefront of system and network research, leveraging the world-leading platforms to solve the challenges problems in this area. The current project team members, from both Microsoft Research Asia – Vancouver and Microsoft Research Redmond labs, have rich experience contributing to both industry and academic community through transferring innovations that support production systems and publications at top conferences.