Applied Scientist 2

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 Applied Scientist II 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.

Responsibilities

• Come up with evaluation techniques, datasets and metrics to measure the impact of the latest models on product scenarios.
• Work with product teams in designing AI-powered experiences.
• Collaborate with research teams to adopt the latest ML technologies into the product.
• Push the boundaries of AI innovation by partnering with platform teams and 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, provide technical guidance to other applied scientists, and act as a mentor
• Participate in onboarding of junior team members and assist in developing academics to the members of multidiscipline teams. You’ll identify new research talent to join Microsoft and collaborate with the academic community to develop the recruiting pipeline.

Qualifications

Required Qualifications:

• Bachelor'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 Master'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 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.

• 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:

• 3+ years of experience in end-to-end development for building, shipping, and iterating on high-impact ML models.
• Proficiency in Python and familiarity with coding in multiple languages.
• Proficiency in using ML libraries from sources such as Hugging Face.
• Expertise in implementing, training, and debugging transformer-based ML models and other related tools and technologies for building and shipping large language models (LLM) applications.
• Published papers in reputed ML conferences and/or contributions to open-source ML projects is a plus.
• Effective communication skills, maintaining customer 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 is a plus.