Responsibilities
As an applied scientist on this team, you’ll help set technical direction and build AI systems that run in production across the infrastructure behind Microsoft 365 and Copilot. You’ll work with large-scale operational data, current AI models, and engineers who know this infrastructure deeply, on problems that affect billions of users.
You will:
Build AI-driven automation, including agentic systems, that manages infrastructure capacity and health at runtime.
Develop models that detect anomalies and emerging issues in large-scale telemetry, often before they affect customers.
Build systems that perform automated root-cause analysis, reasoning across signals, logs, and dependencies to pinpoint why something went wrong.
Design automated mitigation that closes the loop from detection to resolution, reducing reliance on manual intervention.
Develop and scale forecasting models and pipelines that predict capacity needs across Microsoft 365 and Copilot.
Design machine learning and mathematical optimization models that improve the efficiency, reliability, and performance of our services.
Take ideas from prototype to production, turning research into durable systems the business depends on.
Work with engineering, product, and research teams to set priorities and deliver results.
Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a quantitative field in Physics, Chemistry, Biophysics etc. 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 a quantitative field in Physics, Chemistry, Biophysics etc. 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 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
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 thereafter.
- 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.
- 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
- 5+ years experience conducting research as part of a research program (in academic or industry settings).
- 3+ years experience developing and deploying live production systems, as part of a product team.
- 3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
- Experience building machine learning or AI solutions in Python (or C#, C++, R), using modern ML frameworks such as PyTorch or scikit-learn, or LLM-based tools and APIs.
- Working knowledge of SQL or a similar query language.
- Ability to explain technical work clearly to non-specialist audiences and to work well across engineering, product, and research teams.
- Experience building LLM-powered applications and agentic systems, including tool use, retrieval-augmented generation, multi-agent orchestration (for example, Microsoft Agent Framework, Semantic Kernel, AutoGen, or LangGraph), and evaluation of agent quality, cost, and latency in production.
- Experience with anomaly detection, root-cause analysis, AIOps, or automated incident mitigation.
- Experience with time-series forecasting.
- Experience taking ML systems from prototype to production, including pipelines, monitoring, and operating services in the cloud.
- Experience with large-scale data platforms (for example, Azure Data Lake, Spark, Kusto, or Hive).
- Familiarity with mathematical optimization or operations research.
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.
Skills Required
- Bachelor's degree in statistics, econometrics, computer science, electrical or computer engineering, or another quantitative field, plus 6+ years of related experience; or equivalent experience.
- Master's degree in a relevant quantitative field plus 4+ years of related experience; or equivalent experience.
- Doctorate in a relevant quantitative field plus 2+ years of related experience; or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check.
- Master's degree plus 9+ years of related experience, or doctorate plus 6+ years of related experience, or equivalent experience.
- 5+ years of experience creating publications, such as patents, libraries, or peer-reviewed academic papers.
- 2+ years of experience presenting at conferences or other events as an invited speaker.
- 5+ years of experience conducting research in academic or industry settings.
- 3+ years of experience developing and deploying live production systems as part of a product team.
- 3+ years of experience developing and deploying products or systems across multiple product lifecycle stages, from ideation to shipping.
- Experience building machine learning or AI solutions using Python, C#, C++, or R with modern ML frameworks or LLM-based tools and APIs.
- Working knowledge of SQL or a similar query language.
- Experience building LLM-powered applications and agentic systems with tool use, retrieval-augmented generation, multi-agent orchestration, and production evaluation.
- Experience with anomaly detection, root-cause analysis, AIOps, or automated incident mitigation.
- Experience with time-series forecasting.
- Experience taking ML systems from prototype to production, including pipelines, monitoring, and cloud service operations.
- Experience with large-scale data platforms such as Azure Data Lake, Spark, Kusto, or Hive.
- Familiarity with mathematical optimization or operations research.
- Ability to explain technical work to non-specialists and collaborate effectively across engineering, product, and research teams.
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Healthcare Strength — Health coverage is described as comprehensive, with preventive care coverage, vision options, and annual out-of-pocket limits. Feedback suggests medical, mental-health, and disability support are a major strength of the package.
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Parental & Family Support — Family support is expansive, including parental leave, family caregiver leave, child-care assistance, family concierge services, fertility options, and college-advising support for eligible employees. Feedback suggests these benefits meaningfully ease caregiving and family planning demands.
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Wellbeing & Lifestyle Benefits — Wellbeing resources include counseling and employee-assistance services, wellness reimbursements, product discounts, and charitable-matching programs. Feedback suggests these extras complement core benefits and support day-to-day quality of life.
Microsoft Insights
What We Do
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