Overview
Join the Signals Modeling team, part of Microsoft AI Ads Engineering, to shape the future of advanced AI at web scale.
In this role, the Principal Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.
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.
Responsibilities
• Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot. • Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance. • Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. • Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. • Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.
Qualifications
Required Qualifications:
• Bachelors Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) • Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) • Equivalent experience
Preferred Qualifications:
• Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) • Equivalent experience
• Proven experience in programming and data analysis skills • Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM • 6+ years of experience in developing and deploying large-scale machine learning models
Microsoft AI 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: https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.