New 
Senior Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Aug 20, 2025 | |
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OverviewCore Search and AI team (Bing) is looking for people who want to build the next generation of search using advanced AI technologies, especially large language models, at scale. We are responsible for the largest machine learning models at Microsoft by volume and take pride in being the first in the world to solve many practical AI at Scale challenges. Our work spans a very large scope of scenarios including delivering high quality search results from a massive document corpus, query and document understanding, summarization to generate document snippets for representation and ranking, and AI search grounding, etc.As a team, we leverage the diverse backgrounds and experiences of passionate engineers, scientists, and program managers to help us realize our goal of making the world smarter and more productive. We believe great products are built by inclusive teams of customer-obsessed individuals who trust each other and work together closely. We collaborate regularly across the company to find technological breakthroughs from groups like Microsoft Research to infusing AI into the rest of Microsoft products like Office and Azure.Microsoft's mission is to empower every person and every organization on the planet to achieve more, and we believe that artificial intelligence will play a critical role in accomplishing that mission. The Core Search and AI team is the leading applied machine learning team at Microsoft responsible for delivering the highest-quality search experience to over 500M+ monthly active users around the world in Microsoft's search engine, Bing and other dependent search engines such as Yahoo, DuckDuckGo, and new startups like Neeva.
ResponsibilitiesAdvance the state-of-the-art machine learning and NLP algorithms, especially apply LLM models to real-world large-scale search and grounding systems.Work on the full lifecycle of machine learning development including training data collection, feature engineering, model training, offline and online experimentation, and deployment and maintenance. | |