Microsoft Senior Applied Scientist 

United States 

467706062

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.
• A record of publication in top-tier scientific venues (ongoing or in the recent past) (e.g., NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP, KDD, WWW, CHI, PNAS, Nature).
• Experience coding and hands-on experience working with foundation models.
• Experience applying research, preferring the large-scale application of new ideas over theory and prototypes.
• 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.

Other Requirements

• As a part of your application please attach your CV and the names and contact information of at least three established researchers familiar with your research who will be willing to write a letter of reference. One of these people should be your Ph.D. advisor.
• (Optional) A cover letter discussing your interest in the role and how your experience connects with the topics in this call.
• (Optional) A brief academic statement that outlines both your research achievements and agenda and up to two papers that highlight your research interests.

Candidates must be able to meet Microsoft, customer and/or government security screening requirements that are required for this role. These requirements include, but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications

• Experience working on successful applied research projects in industry environments
• Record of publication specifically on applications of language models or very closely related areas
• An applicant with the following skills would be a plus:
  • Applications of Foundation Models
  • Domain Adaptation of Foundation Models (e.g. fine-tuning LLMs/SLMs)
  • Vision, Audio, and Multimodal Foundation Models
  • On-device Foundation Models
  • Trust, Privacy, and Foundation Models
  • Agentic Systems
  • Prompt Tuning
  • Natural Language Processing
  • Applied Machine Learning
  • Data Mining with Language Models
  • Human-AI Interaction
  • Computational Social Science

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• Defining, leading, and helping to conduct research projects that simultaneously advance the state-of-the-art and directly benefit Microsoft’s core productivity products.
• 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.
• Many of the things you will try should lead to unexpected outcomes. You must be comfortable learning from experience, developing new hypotheses, and iterating.
• 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 MSR researchers) throughout the planning and execution of applied research projects, which often involves learning and teaching complex concepts.