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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 Sciences working in OneNote team, your core mission is to contribute on the development of AI features of Copilot Notebooks and OneNote. You’ll be responsible for making sure the State-of-the-Art AI models and capabilities are integrated appropriately with the product to provide value for the customers. 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 will be able to take part in the growth journey of incredible products like Copilot Notebook. You’ll have the opportunity to work teams developing the latest models, research and AI/ML techniques that you can bring to the product teams, as well as opportunities to contribute back to the scientific community (via presentations etc).
Job Responsibility:
Work within and across teams to solve complex technical challenges
Develop best practices around integration of state-of-the-art AI models to build product capabilities and AI features
Write production-quality code, apply debugging best practices, and stay current with industry trends
Defining, leading, and helping to conduct research projects that simultaneously advance the state-of-the-art and directly benefit Microsoft’s core productivity products
Shape product direction by integrating rigorous scientific methods into the product lifecycle
Collaborating and coordinating with people in a range of roles, including researchers, engineers, product managers, designers, and other key product stakeholders
Serving as a bridge between research and product
Teaching, guiding, and tutoring colleagues without research backgrounds in state-of-the-art techniques and research best practices
Sharing your research with others via a range of means, including publication, to enable others to build on your work and to contribute to the understanding of our products as cutting-edge and science driven
Effectively communicating with product leaders (and often Microsoft researchers (MSR)) throughout the planning and execution of applied research projects, which often involves learning and teaching complex concepts
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 7+ 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
At least 4+ years of experience in predictive analytics, statistics, or research
Experience with synthetic data generation and data management for evaluation/training
At least one year of experience publishing patents or peer-reviewed papers
Proficiency in English and cross-functional collaboration
Deep motivation for user-centric AI and interest in human cognition, memory, and AI
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
Prior experience of working with LLM and Gen AI models
At least 6+ years of experience in predictive analytics, statistics, or research
Prior experience of working production grade applications by making use of AI models
Expertise and exposure around the latest developments on the latest developments around the LLM and Gen AI models