It is an exciting time to be building experiences and devices at Microsoft. There is no organization in the world that is better positioned to fundamentally change the way that people live and work. The future of productivity is collaborative, intelligent, and embedded in the world around us. Help shape the rapidly evolving productivity landscape by driving the research program will create the next-generation of intelligent systems and push forward the company's bold ambition for productivity. The Experiences and Devices (E+D) organization at Microsoft is comprised of the company's core productivity products and services, including Office, Windows, Outlook, Teams, Edge, and Surface . As the leader of the E+D Applied Science team your mission will be to build a team that deliver s research that fundamentally impacts these products and services . You will also work with the Applied Science teams within existing E+D product teams to help make Applied Science a fundamental part of every product
Build the E+D Applied Science team. Hire and develop researchers who are not only smart and creative, but also self-driven, curious, and comfortable with ambiguity. Identify the key areas for impact to drive the team's research agenda and enable team members to see their ideas realized in products and services that are used worldwide. Create clarity and coherence for Applied Science across the entire E+D organization. Work with the existing Applied Science teams embedded in our products to define what is expected of the role and its success metrics. Create clear hiring and promotion criteria and
We seek applicants for the Director of Applied Science, E+D from researchers that have a passion and demonstrated ability for growing research teams and supporting complex research agendas. While Applied Science in E+D covers a range of disciplines, the initial focus of the Applied Science team will be machine learning and artificial intelligence, and the directory must be comfortable with a range of topics, including: Machine learning and optimization Deep learning Reinforcement learning Natural language processing Neuro-symbolic systems and reasoning AI fairness, transparency and ethics Program