Microsoft Principal Applied Scientist 

Taiwan, Taoyuan City 

789939809

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field 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 related field 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 3+ years related experience (e.g., statistics, predictive analytics, research)
    
  • OR equivalent experience.
    
• 6+ years of experience in developing and deploying large-scale machine learning models.
  
• 6+ years working experience in statistical natural language processing (NLP) with latest deep learning technologies including transformer and LLMs.
  
• 6+ years working experience with coding in production systems using C++, C#, Java, Python or any other programming language.

Preferred Qualifications:

• Proven experience developing end to end analytics solutions or ML systems for real world applications.
• Proven experience in programming and data analysis skills.
• Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.
• Proven experience in online advertising.

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 October 13, 2025.

• Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions, ad retrieval and relevance across Microsoft Ads and Copilot.
• Design scalable algorithms for online and offline systems, delivering innovative solutions for ad selection, matching quality, and ad generation.
• Drive experimentation through A/B testing and offline validation to evaluate model performance.
• Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.
• Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.