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Microsoft Research Asia Pacific (MSR Asia), established in 1998, is a leading research lab with major sites in Beijing and Shanghai. A group of talented researchers and engineers are working on state-of-the-art technologies every day to solve the most challenging problems in computing and its interdisciplinary areas. As one of the world-class research labs, MSRA offers an exhilarating, supportive, open and inclusive environment for top talents to create the future through their disruptive and cutting-edge research. Over the years, technologies developed by MSR Asia have made a significant impact within Microsoft and also around the world, and new, innovative technologies are constantly being born from the lab. We are seeking exceptional Researchers, Senior Researchers, and Principal Researchers to join our team and drive the next wave of breakthroughs in artificial intelligence. In this role, you will advance the frontier of AI research and build next-generation AI models, systems, and products that reach billions of users worldwide. You will work alongside world-class scientists and engineers in a deeply collaborative, fast-paced environment where intellectual ambition meets real-world impact.
Job Responsibility
Conduct foundational and frontier research in Large Language Models (LLMs), Multimodal Large Language Models, Agentic AI, and AI Systems/Infrastructure — pushing the boundaries of what is possible in model capability, efficiency, and reliability
Design, develop, and evaluate next-generation AI models and systems, from pre-training and post-training methodologies to novel architectures and scalable inference solutions
Conceive and build AI-native products, prototypes, and demos that showcase breakthrough capabilities and translate research insights into tangible user experiences
Collaborate with cross-functional teams across Microsoft — including product engineering, applied science, and platform groups — to transfer cutting-edge research and models into production-quality products at scale
Publish influential research at top-tier venues and contribute to the broader research community through open-source releases, technical blogs, and industry engagement
Identify high-impact research directions by staying at the forefront of the rapidly evolving AI landscape, proactively proposing new initiatives that align with Microsoft's mission and product strategy
Requirements
Bachelor's, Master's, or PhD degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field
Candidates with strong quantitative backgrounds in fundamental disciplines — such as Mathematics, Physics, or Statistics — are equally encouraged to apply
Solid foundation in mathematics (e.g., linear algebra, probability, optimization) with demonstrated analytical and problem-solving skills
Proficient programming skills in one or more of the following: Python, C/C++, or other mainstream languages
Strong self-learning ability and intellectual curiosity, with a track record of quickly mastering new domains, tools, and technologies
Professional working proficiency in English, both written and verbal, sufficient for authoring technical papers, documentation, and cross-team communication
Excellent interpersonal and communication skills, with the ability to collaborate effectively across disciplines, teams, and geographies — both within Microsoft and with external partners and the research community
Nice to have
Research experience in one or more of the following areas: Large Language Models, Natural Language Processing, Computer Vision, Speech/Audio Processing, Multimodal AI, Reinforcement Learning, or AI Systems/Infrastructure
Publication track record at top-tier conferences or journals (e.g., ICLR, NeurIPS, ICML, ACL, EMNLP, CVPR, ICCV)
Hands-on experience with large-scale distributed training, model optimization, or building end-to-end ML pipelines
Familiarity with modern deep learning frameworks (e.g., PyTorch) and large-scale computing environments
Experience shipping AI-powered features or products, demonstrating the ability to bridge the gap between research and production