Principal Applied Scientist

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Are you passionate about creating innovative solutions that empower users to achieve more with Office applications? Do you have a strong background in natural language processing, generative AI, and engineering? If so, we are looking for you to join our team of data and applied science engineers working at the intersection of generative AI and engineering for Office. In this role, you will drive cutting-edge projects, contribute to the Copilot ecosystem, and help shape the Agentic future with one of the most widely used software products in the world.

• • Educational Background: Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Electrical Engineering, or other related technical field (e.g., mathematics, physics, statistics, or similar).
  • Experience: At least 8+ years of industry experience, with strong proficiency in coding in Python for software development and data science. (Experience with additional programming languages is a plus but not required.)
  • Skills: Proficiency in Python-based machine learning frameworks and libraries such as PyTorch and TensorFlow, and experience developing and deploying generative AI or machine learning models into production. Strong communication and presentation skills, with the ability to convey complex technical concepts to diverse audiences.
  • Problem-Solving: Demonstrated ability and motivation to understand complex business contexts and to solve hard, open-ended problems. A proactive mindset in tackling challenges and optimizing solutions to deliver business impact.

• Additional or Preferred Qualifications

  • Advanced Degree (Preferred): Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field and 9+ years of related experience; OR Doctorate in one of the above fields and 6+ years related experience; OR equivalent industry experience.
  • Research & Publications: 5+ years of experience contributing to research publications (e.g., patents, academic papers, open-source libraries) that showcase innovative thinking and technical depth.
  • Research Excellence: 5+ years of experience conducting original research as part of a formal research program (in academic or industrial settings), with proven ability to drive insights from concept to execution.
  • Production Deployment: 3+ years of experience developing and deploying live production systems as part of a product team, ensuring solutions are scalable, reliable, and maintainable.
  • Product Lifecycle Experience: 3+ years of experience contributing to products or systems at multiple stages of the development lifecycle, from initial ideation and prototyping to final production deployment and ongoing iteration.

• • Research and Development: Develop a deep understanding of state-of-the-art tools, technologies, and methods in the research community and product groups. Design and implement fundamental technologies, and drive applied research to enable better search and information retrieval experiences for consumers and enterprises alike.
  • Project Management: Drive projects end-to-end, from design through implementation, experimentation, and ultimately shipping features to users. Own the development of state-of-the-art machine learning and deep learning algorithms leveraging text, images, and video for analyzing and transforming content to build world-class search and AI products.
  • Collaboration: Work in a diverse, geographically distributed team environment where collaboration and innovation are valued. Partner closely with cross-functional stakeholders (engineering, research, product management) to define project goals, success criteria, and deliverables, ensuring alignment and shared vision.
  • Innovation: Stay abreast of the latest research and trends in generative AI, natural language processing (NLP), and related fields. Explore new opportunities and tackle emerging challenges to keep our products on the cutting edge. Lead the team to continuously improve solutions (e.g., enhancing the precision and recall of intelligent systems or bot detection algorithms) by incorporating new signals, data sources, and algorithms.