Member of Technical Staff, LLM Evaluation

As a Member of Technical Staff, LLM Evaluation, you will develop and implement cutting-edge methodologies to help us evaluate how well Copilot performs in real-world usage scenarios. Users turn to Copilot for all types of endeavors, making it critical that we ensure our AI systems effectively help them meet their needs. Our vision for meeting user needs is expansive and includes not only task completion, but also affective aspects of the experience. You will be responsible for developing new methods to evaluate LLMs, train classifiers, experimenting with data collection techniques, and implementing methodologies to provide real-time signals on Copilot performance. We're looking for outstanding individuals with experience in the social sciences, machine learning, and analysis of natural language. The right candidate is a creative problem solver who will work closely with user researchers and product leaders to build automated evaluation frameworks that help us drive improvements in Copilot.  

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Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

• Leverage expertise to measure the performance of Copilot, identify failure modes and novel mitigation strategies, including data mining, prompt engineering, LLM as a judge, and classifier training.
• Creative problem solving, navigating complexity with clarity, independently shaping direction and delivering results even when the path isn’t obvious.
• Create and implement comprehensive evaluation frameworks across diverse scenarios, edge cases, and potential failure modes.
• Build automated testing systems, generalize solutions into repeatable frameworks, and write efficient code for model pipelines and intervention systems.
• Maintain a user-oriented perspective by understanding needs from user perspectives, validating approaches through user research, and serving as a trusted advisor on AI matters
• Track advances in research, identify relevant state-of-the-art techniques, and adapt algorithms to drive innovation in production systems serving millions of users.

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.

Preferred Qualifications: 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Experience prompting and working with large language models.
• Experience writing production-quality Python code.
• Demonstrated interest in Responsible AI. 

Data Science 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

Data Science IC6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 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.