Research Intern - Efficient AI

Overview: Research 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. We are seeing massive growth in AI scenarios and increasing hardware diversity across cloud and edge. Today inference is a major challenge. The shift in trend towards deep learning models and the shift in trend towards large language models has exponentially increased the computation costs. In addition, the continuous evolving landscape, in models and hardware diversity, contributes to the complexity and difficulty of efficient inferencing. Within our Systems Innovation research group, we approach this from a unified perspective of model/system optimization, hardware aware model architectures, and infrastructure optimization at the cloud and edge. We closely collaborate with multiple research teams and product groups across the globe. Some of the research problems we are currently working on include: dynamic model selection, hardware aware Neural Architecture Search (NAS) for large language models; hybrid ML inference that spans cloud and edge; or, analytical performance models for model novel silicon. We are looking for research interns to help advance the state of the art of efficient AI. The ideal candidate will have background in deep learning, model compression, and/or hardware, and the motivation and ambition to apply this in a real-world setting. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.