Microsoft Senior Applied Scientist 

Taiwan, Taoyuan City 

715305069

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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 5+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• Hands on experience training/fine tuning AI/ML models, preferably LLMs/SLMs
• Solid foundational knowledge of statistics and core data science concepts, including data preprocessing, feature engineering, and predictive modeling
• Practical experience in building and optimizing Generative AI pipelines, including techniques like Retrieval-Augmented Generation (RAG), model deployment, function calling, and grounding
• Proficiencyin Python,PyTorch(or equivalent frameworks), and distributed model training
• Solid understanding of data structures, algorithms, and cloud computing principles

Preferred Qualifications:

• 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• Experience with reinforcement learning literature and algorithms.
• Deep knowledge of transformer models and architectures.
• Experience with reinforcement learning algorithms and applications.

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.

• Train and deploy Language Models adapted to specific industry needs.

• Create and adapt novel training and fine-tuning algorithms for language models.

• , 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 byassisting