New 
Applied Scientist II
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 31, 2025 | |
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OverviewMicrosoft AI Web Data team is looking for Applied Scientists to help us build the next generation platform for Bing and Microsoft AI. This is a great opportunity for someone who loves to tackle deep technical challenges and strives for industry-wide impact. An Applied Scientist II in this role would be someone who has proven skills in coding, and have experience in training machine learning/deep learning models, fine-tuning SLMs/LLMs, prompt and agent engineering, data preparation and cleaning, data analysis, Big Data pipelines. In Web Data, we are on a mission to build the most vast and accurate model of the Web to power search and AI. We are pushing frontiers of scalability and index quality by creating models and systems for discovering, storing, processing Web content, and operating AI solutions. 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. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
ResponsibilitiesDiscovering diverse content on the Web quickly and efficiently by understanding the structure and dynamics of the Web and optimizing crawl scheduling.Building Big Data pipelines, creating ML and AI models for index selection, determining document quality, and spam detection.Designing and implementing models and pipelines for near-real time (NRT) indexing and content freshness.Designing and implementing methods for leveraging AI in platform and backend solutions. | |