Microsoft Senior Applied Scientist-Copilot Notebooks 

Taiwan, Taoyuan City 

865823996

Are you passionate about shaping the future applications of AI and empowering millions of users to unlock their full potential? The OneNote team is at the forefront of an exciting transformation with Copilot Notebooks: intelligent, dynamic notebooks infused with powerful AI that act as a true "second brain." Imagine effortlessly capturing ideas, intuitively understanding complex information, and seamlessly taking informed action. This is the heart of our mission.

As a Senior Applied Scientist working in OneNote team, your core mission is to deliver high quality AI-scenarios for Copilot Notebooks. You’ll be responsible for adopting the latest ML technologies, measuring the impact of models and working with product teams to design AI-powered experiences. We are looking for candidates who are creative, self-driven, curious, people-oriented and comfortable defining a path through ambiguity towards high-level goals.

This opportunity will allow you to work in an exciting and fast-paced environment, collaborating closely with teams across multiple organizations and ship products globally. You’ll have access to the latest models, research and ML techniques that you can bring to the product teams, as well as opportunities to contribute back to the scientific community (via presentations etc).

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, 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, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate 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 equivalent experience.
• 3+ years of experience in machine learning, deep learning, natural language processing, computer vision, and/or statistics.
• Expertisein implementing, training, and debugging transformer-based ML models and other related tools and technologies for building and shipping large language models (LLM) applications.
• Proficiencyin Python and familiarity with coding in multiple languages.

Other Requirements:

Candidates must be able to meet Microsoft, customer and/or government security screening requirements that 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:

• Master'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)

• Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.
• 3+years experiencecreating publications (e.g., patents, libraries, peer-reviewed academic papers).
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• 3+years experienceconducting research as part of a research program (in academic or industry settings).
• 1+ year(s) experience developing and deploying live production systems, as part of a product team.
• 1+ year(s) experience developing and deploying products or systems at multiple points in the productcyclefrom ideation to shipping.
• 5+ years of experience in end-to-end development for building, shipping, and iterating on high-impact ML models.
• Proficiencyin using ML libraries from sources such as Hugging Face.
• Published papers in reputed ML conferencesand/or contributions to open-source ML projects.
• Effective communication skills,maintainingcustomer experience and quality along with the ability to work across groups and disciplines.
• Ability to quickly ramp up on various domains within Machine Learning.
• Experience shipping high-quality products at scale.

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

• Come up withevaluation techniques,datasetsandmetricsto measure the impact ofthe latestmodelson product scenarios.
• Work with product teamsindesigningAI-powered experiences.
• Collaborate with research teams to adopt the latestMLtechnologiesinto the product.
• Push the boundaries of AIinnovation by partnering withplatformteamsand working with frontier models.
• Build and deploy Machine Learning (ML) models, create data pipelines, and manage training and test datasets.
• Foster a healthy and inclusive team environment,providetechnical guidance to other applied scientists, and act as a mentor.
• Participate in onboarding of team members andassistin developing academicstothemembers ofmultidisciplineteams.You’llidentifynew research talent to join Microsoft and collaborate with the academic community to develop the recruiting pipeline.