Microsoft Principal Applied Scientist 

United States, Washington 

653178693

They will heavily use the recent advances in grid or cloud computing infrastructure to harness hugeof data for solving many of the above-mentioned problems andlarge language models (LLM) for many of the problems.

Required Qualifications:

• Bachelor's Degree in Artificial Intelligence, Statistics, Computer Science or related field AND 6+ years related experience (e.g.Machine Learning, Deep Learning, NLP, Computer Vision)
  • ORMaster's Degreein Machine Learning Artificial Intelligence, Statistics, ComputerScienceor related field with 4+ years related experience (e.g.Machine Learning, Deep Learning, NLP, Computer Vision)
  • OR Doctorate in Artificial Intelligence, Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., Machine Learning, Deep Learning, NLP, Statistics, Computer Science)
  • OR equivalent experience.

• 6+ years of experience in machine learning, deep learning, Natural Language Processing, computer vision and/or statistics.
• 5+ years’ experience in software development.

Preferred Qualifications

• MS/PhD degree in CS/EE or related areas is preferred
• Effective communication skills, both verbal and written
• Familiarity with distributed data processing/analysis and modeling paradigm.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until September 3, 2024.

online advertising platform and service. Microsoft's advertising team is at the core of this effort, responsible for research & development of all the algorithmic components in our paid search advertising technology stack, including:

• Creative Quality Modeling (Clickbait, Perceived/Actual Relevance, Image Quality, Policies etc.)
• User response (click, wins & conversion) prediction using large scale machine learning algorithms
• Bidder/PublisherOptimization
• Advertising metrics and measurement
• Data mining and analytics
• Experimentation infrastructure including tools for configuring and launching experiments, dashboard, live marketplace monitoring, and diagnosis.
• Embody our