Microsoft
Principal Applied Scientist
$143K–$304K
Redmond, WA +1 · On-site · Principal · Full-time · Posted Oct 8, 2026
- Location
- Redmond, WA
Mountain View, CA - Experience
- 6+ years with a bachelor’s degree; or 4+ years with a master’s degree; or 3+ years with a doctorate; or equivalent experience. Preferred: master’s and 9+ years, or doctorate and 6+ years, or equivalent experience.
- Education
- Bachelor’s, master’s, or doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field; or equivalent experience.
About the job
Leads the design, deployment, and operation of scalable machine-learning systems that detect and stop advertising fraud in real time, while providing technical leadership and mentorship.
What you'll do
- Lead fraud-detection initiatives and build production-ready ML solutions, including anomaly detection, cross-signal analysis, and low-latency pipelines.
- Validate, deploy, monitor, and continuously optimize systems for reliability, effectiveness, latency, and cost.
- Guide technical direction and cross-functional collaboration; mentor scientists and promote scientific rigor and responsible AI.
What they ask for
- Bachelor’s degree in a listed or related field and 6+ years of related experience; or a master’s degree in a listed or related field and 4+ years; or a doctorate in a listed or related field and 3+ years; or equivalent experience.
- Meet Microsoft, customer and/or government security screening requirements, including the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Nice to have
- Master’s degree and 9+ years of related experience, or doctorate and 6+ years, or equivalent experience.
- Experience with ML research and publications, production systems, technical leadership, scalable ML systems, and mentoring scientists.
Pay
USD $142,800 - $274,800 per year (base salary); USD $188,000 - $304,200 per year (base salary)
Tools
machine learning (ML), anomaly detection, cross-signal analysis, large language models (LLMs)
AI focus
Develop and operate production-scale AI/ML fraud detection, using anomaly detection, cross-signal analysis, LLMs, and other modern AI techniques.
Model-written summary · the original posting is authoritative