Senior Applied Scientist

Senior Applied Scientist

Requirements

• Doctorate (or currently pursuing) in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field 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.
• Ability to apply 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.

Responsibilities

• 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.

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 applicants will come 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