Senior Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Jul 25, 2025 | |
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OverviewThe Microsoft Applied Sciences Group incubates disruptive technologies for Microsoft's next-gen hardware products and is working on several exciting projects that will shape how computers and other devices perceive the user and the user's environment. Operating as a startup within the company, this team works closely with several research and product teams to bring compelling new experiences to the market. A lot of these experiences will be powered by large language models, NLP, speech, and computer vision - and as part of this team, you will have the unique opportunity to develop and implementing the ML algorithms and DNN models that make magic happen!We are looking for a Senior Applied Scientist Applied Science in the field of LLM and SLM, which involves expertise in model distillation, low-rank adaptation, muti-modal adapter, and deep learning techniques to help our devices understand the user intents and execute a series of actions to complete the tasks in a computer environment. The ability to analyze multimodal data and interpret various human and human-object interactions is key to Applied Sciences' mission of enabling a seamless set of human computer interactions. As part of this team, you will be working with a growing team of talented researchers already dedicated to this mission and use data and hardware only available to a select few. Naturally, the opportunity for you to push the state of the art in this field is huge. 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.
ResponsibilitiesResearch and develop LLMs and SLMs with Python and other relevant programming languages.Train, distill, and finetune deep learning models in TensorFlow and PyTorch, including data engineering.Build pipelines to test algorithms and models and analyze the results.Optimize algorithms and models for speed and accuracy on target hardware. | |