Principal Applied Scientist
 Microsoft | |
 United States, California, Mountain View | |
 Oct 04, 2024 | |
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OverviewWe are looking for a Principal Applied Scientist in Redmond, WA or Mountain View, CA, with a background in Machine Learning(ML), Generative AI (Artificial Intelligence), Data Science, Data Mining, or related fields.Candidates should have a keen interest in artificial intelligence and optimization at the web scale. They will play a key role in driving algorithmic improvements to online and offline systems, develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually improve our KPIs. The Search and AI organization includes the product, engineering, and science teams working towards making Microsoft's Bing search engine globally state of the art. Our mission is to delight users everywhere with the best search experience. We are focused on creating competitive and differentiated search quality experiences, which we do by applying highly advanced ML technologies such as large-scale deep learning models and by investing in more modern search experiences. 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. Our Culture:Microsoft Culture Some work from our team: Introducing Bing generative search | Bing Search Blog Microsoft unveils Bing Generative Search - enhanced with AI, it's a complete overhaul of traditional search | Windows Central
ResponsibilitiesBuilding and owning production machine learning models to improve resultsWorking hands on with state of art generative models like GPT, Llama, Mistral, and others, to deliver big impactFinding insights and forming hypothesis on large-scale data with various machine learning, feature engineering, statistical, and data mining techniques: e.g. regression, classification, NLP, optimization.Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from themWrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. All programming languages are welcome, especially Python, C#, R, C++, Java, and SQLTaking complex problems and the associated data and giving the answers in a concise form to assist executives in making key business decisionsOtherEmbody our Culture & Values | |