New 
Principal Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 18, 2025 | |
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OverviewJoin Microsoft's CoreAI - AI Platform team in Bay Area/Redmond to build the AI Data Platform, the foundation for secure, scalable, reusable datasets that power model development. We are seeking Principal Applied Scientists to drive scientific innovation in data generation, validation, evaluation, and automation. You will set the vision for intelligent, ML-driven services that manage the end-to-end data lifecycle, and partner with leaders across Microsoft to ensure Microsoft's data investments deliver maximum AI impact. Our mission is to build a central AI data platform that breaks down Microsoft's data silos and manages the full lifecycle of first-party, third-party, synthetic, and human-labeled data, accelerating AI model development with secure, reusable, and compliant datasets. The Principal Applied Scientist in AI Data Platform is responsible for driving scientific innovation in data generation, validation, evaluation, and automation, setting the vision for intelligent, ML-driven services that manage the end-to-end data lifecycle, and partnering with leaders across Microsoft to ensure Microsoft's data investments deliver maximum AI impact.
Responsibilities Define the scientific vision and roadmapfor ML- and agent-driven automation of the dataset lifecycle, including ingestion, validation, PII detection and handling, governance, discovery, and feedback loops. Lead the design and deployment of advanced ML pipelinesfor synthetic data generation, augmentation, and human-in-the-loop workflows. Establish evaluation methodologiesto measure dataset quality, coverage, and downstream impact on large-scale model training. Advance state-of-the-art methodsfor data-centric AI, including LLM-based evaluation, gap mining, and bias/fairness detection. Mentor and grow a team of applied scientists, providing technical leadership and fostering a culture of excellence. Collaborate with engineering leadersto integrate research into scalable, production-ready platform services. Influence Microsoft's AI strategyby shaping best practices for data-driven model development and sharing learnings internally and externally. | |