Within our Microsoft wide Systems Innovation initiative, we are working to advance efficiency across AI systems, where we look at novel designs and optimizations across AI stacks: models, AI frameworks, cloud infrastructure, and hardware. We are an Applied Research team driving mid- and long-term product innovations. We closely collaborate with multiple research teams and product groups across the globe who bring a multitude of technical knowledge in cloud systems, machine learning and software engineering. We communicate our research both internally and externally through academic publications, open-source releases, blog posts, patents, and industry conferences. Further, we also collaborate with academic and industry partners to advance the state of the art and target material product impact that will affect 100s of millions of customers.
We are looking for a Senior Researcher – LLM Systems to invent, analyze, and productionize the next generation of serving architectures for transformer-based models across cloud and edge. The candidate will focus on algorithmic and systems innovations, including batching, routing, scheduling, caching, deployment safety, and endpoint configuration, that materially improve latency, throughput, cost, and reliability under real-world SLAs for Microsoft Copilots.
The qualified candidate brings a solid background in distributed systems, operating systems, and/or large-scale ML serving, plus the ambition to translate research into impact in production environments. This role blends rigorous research (theory + measurement) with hands-on engineering, and includes publishing papers, filing patents, and collaborating across research and product teams to advance the state of the art.
Have a look at this link for reading: Efficient AI - Microsoft Research
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