Principal Applied Scientist

Overview

At Microsoft AI, we're building the systems that help the world discover, understand, and benefit from information at unprecedented scale. The Web Data Platform (WDP) sits at the foundation of Bing, Copilot, and Microsoft's AI ecosystem. Every day, our platform processes and understands vast amounts of information from across the open web, transforming raw content into the trusted knowledge that powers search, AI reasoning, and next-generation digital experiences.

We're entering a new era where AI is not only consuming information, but also shaping how knowledge is created, discovered, and trusted. The opportunities are immense, and so are the challenges. As the volume of content on the web continues to accelerate, ensuring quality, trustworthiness, and relevance has become one of the defining technical problems of our time.

As a Principal Applied Scientist, you will help define how the world's information ecosystem evolves in the age of AI. You'll work at the intersection of large-scale machine learning, web understanding, information retrieval, and generative AI to solve problems that impact billions of users and millions of creators.

You will join a team that is pushing the boundaries of what is possible in AI-powered content understanding, web-scale intelligence, and trustworthy information systems. From advancing the state of the art in content quality and knowledge discovery, to helping safeguard users from abuse, deception, and emerging ecosystem risks, your work will help shape how people experience information in the AI era.

This is an opportunity to tackle some of the hardest technical challenges in the industry while helping build a healthier, more trustworthy, and more useful web for everyone.

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

• Design, develop, and deploy state-of-the-art machine learning, information retrieval, large language model, and agentic AI solutions that improve the quality, understanding, and usefulness of web-scale content and knowledge systems.
• Drive scientific strategy and technical direction for large-scale machine learning and AI initiatives across Web Data Platform.
• Lead end-to-end development of scientific solutions, including problem formulation, experimentation, model development, evaluation, production deployment, and long-term measurement of impact.
• Partner closely with engineers, product managers, researchers, and leaders across Bing, Copilot, and Microsoft AI to solve challenging customer and platform problems.
• Define long-term technical roadmaps, influence organizational investments, and identify new opportunities where advances in AI can create meaningful customer value.
• Establish rigorous experimentation frameworks, evaluation methodologies, and success metrics to drive scientific excellence and measurable product impact.
• Advance technologies that increase trust, quality, integrity, and safety across the web ecosystem, helping ensure that Microsoft experiences surface authoritative, useful, and reliable information while mitigating abuse, manipulation, spam, fraud, and emerging forms of low-quality AI-generated content.
• Develop novel approaches for content understanding, quality estimation, risk detection, trust modeling, and ecosystem health measurement at Web scale.
• Mentor and grow other scientists, raise the scientific bar across the organization, and contribute to recruiting and cultivating world-class talent.
• Drive cross-organizational collaboration and influence across teams, helping shape technical strategy beyond your immediate area of ownership.

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.

Preferred Qualifications

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• Proven track record of shipping machine learning or AI capabilities that operate at internet scale and directly impact product quality, customer satisfaction, or business outcomes.
• Experience developing ranking, retrieval, classification, quality, trust, safety, spam, abuse, content understanding, or recommendation systems.
• Hands-on experience with modern AI systems including foundation models, LLMs, SLMs, agents, tool use, evaluation frameworks, and prompt engineering.
• Experience with distributed data processing and model training using large-scale compute platforms.
• Experience applying Responsible AI, model governance, experimentation, and online measurement methodologies.
• Solid software engineering skills in Python, C++, C#, Java, or similar languages.
• Experience leading cross-organizational technical initiatives and influencing engineering and product direction without direct authority.
• Publications, patents, or recognized technical contributions in machine learning, information retrieval, search, NLP, GenAI, or related fields.
• Demonstrated experience mentoring senior scientists and raising scientific rigor across an organization.

• #AIX
• #MicrosoftAI

Pay and benefits

Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $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:

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.