Drimva

Microsoft

Principal Applied Scientist - CoreAI

$143K–$331K

Redmond, WA +4 · On-site · Principal · Full-time · Posted Mar 30, 2026

Location
Redmond, WA
Garden City, NY
San Francisco, CA
Mountain View, CA
Boston, MA
Experience
6+ years with a Bachelor's degree, 4+ years with a Master's degree, or 3+ years with a Doctorate; equivalent experience accepted. Preferred: 5+ years in research/ML engineering or applied research scientist roles.
Education
Bachelor's, Master's, or Doctorate in Computer Science, Computational Linguistics, or related field; or equivalent experience.

About the job

Develops and deploys machine learning techniques and responsible AI systems focused on safety, alignment, and trustworthiness, from experimentation through production monitoring and iteration.

What you'll do

  • Develop machine learning techniques advancing AI safety, alignment, and trustworthiness.
  • Collaborate across product, research, and engineering teams to build and maintain responsible AI systems.
  • Support systems throughout experimentation, production, monitoring, and continuous iteration.

What they ask for

  • Bachelor's degree in Computer Science, Computational Linguistics, or related field and 6+ years of related experience; or Master's degree in a stated or related field and 4+ years; or Doctorate in a stated or related field and 3+ years; or equivalent experience.
  • Meet Microsoft, customer and/or government security screening requirements, including the Microsoft Cloud Background Check.

Nice to have

  • Experience and familiarity with large language models (LLMs).
  • Experience with distributed systems, algorithms, software engineering, deep learning, transformer models, or LLM training and fine-tuning; 5+ years in research/ML engineering or applied research, ideally focused on AI safety.

Pay

USD $142,800 - $274,800 per year (base salary); USD $188,000 - $304,200 per year (base salary); USD $165,600 - $296,400 per year (base salary); USD $220,800 - $331,200 per year (base salary)

Tools

machine learning, large language models (LLMs), deep learning, transformer-based models, distributed systems, Azure

AI focus

Develops AI safety, alignment, and trustworthy AI techniques and responsible AI systems, including work from experimentation through production and monitoring.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)