Microsoft Applied Scientist II 

Taiwan, Taoyuan City 

577242591

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Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
  • OR equivalent experience.
• 2+ years of industry experience in applied machine learning or data science roles.
• Proficiency in Python and ML libraries such as PyTorch or TensorFlow.
• Experience developing and evaluating generative AI models.
• Familiarity with NLP techniques and content understanding.

Preferred Qualifications:

• Solid verbal and written communication skills to explain complex technical concepts to diverse audiences.
• Ability to tackle open-ended problems and deliver practical, scalable solutions.
• Experience deploying ML models in production environments.
• Exposure to full product lifecycle from prototyping to deployment and iteration.
• Contributions to research publications, patents, or open-source projects.

• Applied Research & Development: Contribute to the design and implementation of machine learning models and algorithms for search, summarization, and content understanding in Office applications.
• Model Development: Build and fine-tune ML/DL models using frameworks like PyTorch or TensorFlow. Collaborate on deploying models in production environments with a focus on scalability and performance.
• Cross-Functional Collaboration: Work closely with engineering, product, and research teams to translate business needs into technical solutions and deliver impactful features.
• Experimentation & Evaluation: Conduct experiments, analyze results, and iterate on solutions to improve precision, recall, and user satisfaction.
• Innovation: Stay current with research trends in generative AI and NLP. Explore new signals, data sources, and modeling techniques to evolve intelligent systems and contribute to the Copilot ecosystem.