Microsoft Senior Applied Scientist 

Taiwan, Taoyuan City 

75569982

Required/Minimum Qualifications:

• Bachelor's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
  • OR Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• 2+ years of experience training/fine tuning AI/ML models, preferably LLMs/SLMs (slow learning model).
  
• 2+ years of experience building Generative AI pipelines, e.g. with RAG (Retrieval augmented generation).
  
• 2+ years of experience with Python and/or PyTorch.

Other Requirements

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Doctorate in relevant field OR equivalent experience.
• Deep knowledge of transformer models and architectures.
  
• Experience with reinforcement learning algorithms and applications.
  
• Experience working with customers deploying AI solutions.

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 July 23, 2025.

• Train and deploy Language Models adapted to specific industry needs.
• Create and adapt novel training and fine-tuning algorithms for language models.
• Identifies, researches, and implements machine learning solutions given product requirements.
• Brings a research project to successful completion yielding new algorithms, prototypes, theories, tools, methods, analyses, insights, or collections of data which solve one or more open research problems.
• Document and share best practices across the organization.
• Supports mentorship by assisting with onboarding of research interns or other early in career team members.