Research Sciences INTERN
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Do you enjoy shaping frontier AI technologies such as AI agents and agent evaluation, one of the fastest-growing areas in AI today? Join our team to help build the data-driven intelligence behind Microsoft 365 Copilot, applying advanced analytics and machine learning to improve the quality, intelligence, and user experience of AI-powered productivity solutions.
As an Applied Scientist, you'll work at the intersection of large language models (LLMs), information retrieval, search, machine learning, and AI evaluation, partnering closely with software engineers, researchers, and product managers to set scientific direction and lead the development of data-driven approaches that measure, analyze, and improve AI systems. You'll analyze large-scale datasets, design rigorous experiments, uncover actionable insights, mentor other scientists, and drive cutting-edge AI innovations from idea to production.
Our team embraces an AI-first engineering culture, leveraging AI throughout the development lifecycle to accelerate innovation while maintaining the highest standards of security, quality, and trust.
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.
Lead the development of metrics and evaluation methodologies to measure the quality, accuracy, and usability of AI systems.
Design and analyze online and offline experiments to quantify product improvements and identify opportunities for optimization.
Build scalable data pipelines, dashboards, and analytical tools that enable continuous quality monitoring.
Apply statistical analysis, machine learning, and data mining techniques to extract insights from large-scale datasets.
Partner with engineering, research, and product teams to shape technical direction and prioritize investments using data-driven recommendations.
Investigate quality regressions, identify root causes, and propose measurable improvements.
Shape best practices for AI evaluation, experimentation, and responsible AI measurement across multiple products, mentoring scientists in their adoption.
Communicate technical findings clearly to both engineering and business stakeholders.
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:
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.
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Microsoft builds Windows, Azure, Office and the Copilot family of AI assistants, and operates one of the largest AI training and inference fleets in the world. Microsoft Research and the AI platform teams work across foundation models, systems for large-scale training, and applied ML in every product line.
Founded in 1975 and headquartered in Redmond, Washington, the company is also OpenAI's principal compute partner and ships AI tooling for developers through GitHub, VS Code and Azure AI.
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