Microsoft Principal Applied Scientist 

Taiwan, Taoyuan City 

798994286

Required/Minimum Qualifications

• Doctorate in relevant field AND 3+ years related-research experience
  • OR equivalent experience.

• 3+ years of experience in machine learning, deep learning and/or related fields.
• 3+ years of experience in software development experience in languages such as Python, Java, C++, Scala, or C#.
• 3+ years of experience in data science and data reporting.

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.

Additional or Preferred Qualifications

• Doctorate in relevant field AND 5+ years related-research experience
  • OR equivalent experience.
• Experience publishing academic papers as a lead author or essential contributor.
• Experience participating in a top conference in relevant-research domain.

• 3+ year experience developing end to end Machine Learning/Deep Learning (ML/DL) engineering systems.
• 3+ year experience in distributed/cloud computing systems (e.g. Spark, Hadoop, Azure, AWS, Cosmos).
• Experience working in the Gen Artificial Intelligence (AI) field.
• Experience developing and designing science models consumed in a production development.
• Experience working through full product cycles from initial design to final product delivery.

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 March 24, 2025.

You will be a technical leader, working closely with other leaders, colleagues, and customers from various business domains to drive Responsible AI product innovation.

• Drive innovations in AI Safety models and algorithms, keeping engineering resource consumption in mind.
• Lead and participate in design, implementation, and execution across a variety of features including analyzing Machine Learning/Deep Learning (ML/DL) models and creating actionable, data-driven insights.
• Analyze complex, high-volume, high-dimensionality data.
• Collaborate with a team of world-class scientists and engineers to solve very challenging problems.
• Invest in others’ growth.
• This role requires a deep understanding of generative AI use cases and responsible AI, a keen sense of model development to support responsible AI commitments while keeping product innovation in mind, and a technical background to develop responsible AI measurement and mitigation techniques.
• Embody our and