New 
Senior Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 10, 2025 | |
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OverviewAs a Senior Applied Scientist for the Customer Service Applications Team, you will play a pivotal role in advancing Microsoft's mission to empower every individual and organization on the planet to achieve more. You will contribute to the development and integration of cutting-edge AI technologies into Microsoft products and services, ensuring they are inclusive, ethical, and impactful. You will collaborate across product, research and engineering teams to bring innovative solutions to life, applying your experience in machine learning, data science, and AI to solve complex problems. Your work will directly influence product direction and customer experience. We are in an era of unprecedented innovation and openness. As Microsoft continues to advance AI, we are seeking individuals to help address some of the most exciting topics in the field. Our vision is to build a truly open architecture platform that enables users to summon tailored AI agents to drive real-world outcomes. Join us in shaping the future of AI agents. 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.
ResponsibilitiesBuild collaborative relationships with product and business groups to deliver AI-driven impacts. Research and implement state-of-the-art technology using foundation models, prompt engineering, Retrieval-Augmented Generation (RAG), graphs, multi-agent architecture, and classical machine learning techniques. Fine-tune foundation models using domain-specific datasets. Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, online experiments, and return on investment analysis. Build rapid AI solution prototypes and contribute to production deployment of these solutions, debug production code, and support MLOps/AIOps. Demonstrate deep experience in AI subfields (e.g., deep learning, Generative AI, Natural Language Processing (NLP), muti-modal models) to translate cutting-edge research into practical, real-world solutions that drive product and business impact. Apply a deep understanding of fairness and bias in AI by proactively identifying ethical and security risks including XPIA (Cross-Prompt Injection Attack) unfairness, bias, and privacy concerns to ensure equitable and responsible outcomes. Ensure responsible AI practices throughout the development lifecycle, from data collection to deployment and monitoring. Embody our Culture and Values. | |