Senior Applied Scientist-Word

The Microsoft Word Writing Assistance and Language Intelligence team located in Redmond, Washington build large scale natural language understanding and natural language generation models using cutting edge Natural Language Processing technologies and advanced linguistic knowledge. The team has a 25-year track record of delivering innovative AI-powered writing assistance solutions to millions of users worldwide with a vision of bringing out the best writer in everyone. The team have recently launched a set of groundbreaking Copilot features that help users to dramatically enhance productivity and creativity throughout their writing journey from start to finish.   

As a Senior Applied Scientist in the team, you will drive intelligence experience projects through their entire life cycle from idea creation through rigorous science experiments, evaluations, and finally to worldwide availability. You will collaborate with other applied scientists, researchers, engineers, and product managers to deliver high-quality features and products that enhance the writing experience across multiple platforms and domains. You will also conduct cutting-edge applied research leading to high product impact and publish your work in top-tier conferences and journals. This opportunity will allow you to accelerate your career growth, develop deep business acumen, and hone your scientific skills. You will have the flexibility to work from home partially or fully, depending on your preference and location. We value work-life balance and support our team members to achieve their personal and professional goals. 

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. 

Required Qualifications:

• 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.
• 3+ years of research or product experience in NLP. 
• 3+ years of hands-on experience in Deep Learning using PyTorch or similar. 
• 3+ years of software engineering experience in Python or C#. 

Preferred Qualifications:

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 
• 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers). 
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker. 
• 3+ years experience conducting research as part of a research program (in academic or industry settings). 
• 1+ year(s) experience developing and deploying live production systems, as part of a product team. 
• 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping. 
• PhD degree in Computational Linguistics or Computer Science with a focus on NLP. 
• Fluency with recent NLP & LLM advancement as well as a driven passion for discovering the next generation of technology. 
• Experience conducting applied research and publishing papers. 
• Experience working in collaborative multiple team environment and ship production features in a fast-paced environment. 
• Effective communication, collaboration, and problem-solving skills and a customer-centric mindset. 

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay 

Microsoft will accept applications for the role until July 8th, 2025. 

The mission of the team is to advance intelligent reading and writing assistance in M365 and to make fundamental contributions to advancing the state-of-the-art in language technology within Microsoft and in industry. As a senioar applied scientist, your responsibilities include: 

• You will review business and product requirements and incorporate state-of-the-art research to formulate plans that will meet business goals.  
• You will research and develop an understanding of tools, technologies, and methods being used in the community that can be utilized to improve product quality, performance, or efficiency.  
• You will stay updated with the latest research and trends in NLP and related fields and explore new ideas and opportunities for innovation.  
• You will participate in onboarding of team members. You’ll identify new research talent to join Microsoft and collaborate with the academic community to develop the recruiting pipeline.  
• You will document work in progress and experimentation results and share findings to promote innovation. You’ll also use your deep understanding of fairness and bias to contribute to ethics and privacy policies related to research processes and data collection.