We use cookies. Find out more about it here. By continuing to browse this site you are agreeing to our use of cookies.
#alert
Back to search results

Principal Applied Scientist, AI Data Platform (CoreAI)

Microsoft
United States, Washington, Redmond
Sep 21, 2025
OverviewJoin Microsoft's CoreAI team to build the AI Data Platform, the foundation for secure, scalable, reusable datasets that power model development. The AI Data Platform team's 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 AI Data Platform team is responsible for large-scale data infrastructure, automation tools, and intelligence services to transform how Microsoft collects, generates, manages, and shares AI training data. 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.
Responsibilities Drive 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. 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.
Applied = 0

(web-759df7d4f5-28ndr)