Microsoft
Principal Applied Scientist
$143K–$304K
Redmond, WA · On-site · Principal · Full-time · Posted Oct 8, 2026
- Experience
- 6+ years with a bachelor’s degree, 4+ years with a master’s degree, or 3+ years with a doctorate; or equivalent experience. Preferred: 9+ years with a master’s degree or 6+ years with a doctorate, or equivalent experience.
- Education
- Bachelor's, master's, or doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field; or equivalent experience.
About the job
Leads scientific strategy and develops web-scale AI and machine-learning systems that improve content quality, trust, safety, and information discovery across Microsoft experiences.
What you'll do
- Design, deploy, and measure machine-learning, retrieval, LLM, and agentic AI solutions for web-scale content and knowledge systems.
- Set scientific strategy and roadmaps, lead end-to-end research and production work, and establish evaluation methods and success metrics.
- Collaborate across teams, mentor scientists, and advance systems for content quality, trust, safety, and ecosystem risk detection.
What they ask for
- Bachelor’s degree in a listed or related field and 6+ years of related experience, or master’s degree and 4+ years, or doctorate and 3+ years, or equivalent experience.
- Proven track record shipping machine-learning or AI capabilities at internet scale with product, customer, or business impact.
- Experience with distributed data processing and model training using large-scale compute platforms.
- Solid software engineering skills in Python, C++, C#, Java, or similar languages.
Nice to have
- Experience developing ranking, retrieval, classification, quality, trust, safety, spam, abuse, content understanding, or recommendation systems.
- Hands-on experience with foundation models, LLMs, SLMs, agents, tool use, evaluation frameworks, and prompt engineering.
Pay
USD $142,800 - $274,800 per year base salary; USD $188,000 - $304,200 per year base salary
Tools
Python, C++, C#, Java, LLMs, SLMs
AI focus
Develops machine learning, information retrieval, large language model, and agentic AI solutions for web-scale content understanding, quality, trust, safety, and risk detection.
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