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Join an innovative team that delivers core Copilot Shared Services for our flagship Office Apps such as Word, Excel, and PowerPoint. Our mission is to deliver the next generation of personalized Copilot experiences leveraging best of breed Microsoft technologies across Copilot Platform, Microsoft Substrate, and beyond. Consider this opportunity to advance our approach in ways that benefits millions of people. We will achieve this through innovation and vision for our next-gen solutions, connecting key partnerships across Microsoft, and influencing best-of-breed advancements leveraging AI technology. Within Copilot Shared Services, we apply new foundational LLMs, create advanced ML techniques, develop rich algorithms, and leverage AI and the skills of Applied Science to accelerate developmental advancements and improve quality of our customer experiences. We invest in agentic solutions and are working to advance methods of evaluation and automated customer solutions. We are looking for a Senior Applied Scientist to join our team to help establish the vision of the future. In this role, you’ll work closely with engineers, program managers, data scientists and applied scientists to improve our approach to personalized experiences, best leverage and fine tune foundational models, advance evaluation techniques, and improve engineering productivity.
Job Responsibility:
Define, lead, and help to conduct research projects and workstreams that directly benefit our customers, drive positive usage, and improve Microsoft’s core productivity products
Formulation of advanced prompt engineering, selecting and fine-tuning LLMs, designing and managing evaluation datasets, develop concepts for more efficient and accurate solutions, and researching and assessing different architectures and approaches from across the M365 ecosystem
Collaborate and coordinate with people in a range of roles, including researchers, engineers, product managers, designers, and product leaders and other key product stakeholders
Generate ML / AI based models that can be shipped to customers to improve their experience and used internally to generate data insights to shape the features and products we ship to customers
Teach, guide, and tutor colleagues without research backgrounds in state-of-the-art techniques and research best practices
Many of the things you will try should lead to unexpected outcomes. You must be comfortable learning from experience, developing new hypotheses, and iterating
Share project outcomes and insights 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
Requirements:
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
1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping
3+ years of experience in machine learning, deep learning, natural language processing, computer vision, and/or statistics
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
Ability to apply research, preferring the large-scale application of new ideas over theory and prototypes
Experience working on successful applied research projects in industry environments
Experience coding and hands-on experience working with foundation models
Demonstrated collaboration and communication skills, both within-team and cross-team, and experience working through problems in ambiguous environments adapting to new research challenges as technology develops