Microsoft Applied Scientist - LLM 

Taiwan, Taoyuan City 

301813644

Required Qualifications:

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, data modeling or data engineering work
  • OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field
  • OR equivalent experience.
• Expertise in various ML frameworks and libraries (Scikit-learn, PyTorch/TensorFlow, Azure ML, OpenAI, HuggingFace).

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:

• Fluency with recent NLP & ML advancements e.g. large language models, as well as a driven passion for discovering the next generation of technology.
• Experience working on Machine Translation or language-related tasks would offer a distinct advantage.
  
• Excellent knowledge of experimental design and evaluation.
  
• Experience working in a technical problem domain (plan, design, execution, continuous release, and service operation).
  
• Excellent research skills and experience in bringing cutting-edge research ideas into production to deliver business impact.
  
• Proven track record of shipping Machine Learning/AI features.
  
• Excellent communication skills, inter-personal & collaboration skills.
• Proficiency with large data sets (structured and unstructured), relational databases, database-design and ELT.

• Investigate, design, prototype, test, validate and deliver machine learning/AI localization features using best in class technologies and frameworks.
• Collaborate with multiple disciplines: Product Managers, Applied & Data Scientists, Software Engineers, and partner teams to deliver and contribute to solutions.
• Leverage Azure services (e.g., Azure ML, Azure DevOps, Azure Data Factory) and develop customized modules to instrument MLOps to monitor, adjust and improve our services.
• Support and manage machine learning models, production pipeline, and experimentation platform, contributing to all stages of model development, deployment and monitoring.