Microsoft Principal Applied Scientist AI Data Platform CoreAI 

Taiwan, Taoyuan City 

642568760

datasets that power model.

is to build aingAI modelwith 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.

Required Qualifications

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
• Experience applying ML/AI to real-world problems.
• Experience leading applied science projects from concept to production.
• Programming experience in Python and ML frameworks.
• Demonstratedexpertisein data quality, dataset evaluation, or synthetic data generation.

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years

Preferred Qualifications

• PhD in Computer Science, Machine Learning, Statistics, or related field, or equivalent experience.
• Experience with LLMs, data-centric AI approaches, or intelligent agent-based systems.
• Knowledge of data privacy, compliance, and governance in large-scale AI systems.
• Familiarity with distributed data systems (e.g., Spark, Databricks, Azure Data Lake).
• Strong publication record in top ML/AI conferences (NeurIPS, ICML, KDD,ICLRetc.).
• Ability to influence cross-functional strategy and collaborate effectively with product, research, and engineering leader

Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft posts positions for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

• scientific innovation in data generation, validation, evaluation, and automation,settingthe vision for intelligent, ML-driven services that manage the end-to-end data lifecycle, and partneringwith 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.
• Advancestate-of-the-artmethodsfor 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.