Microsoft Senior Applied Scientist 

United States, Washington 

197018997

and Intelligenceis responsible forthe moderation and understanding ofews feedto delight our end-userby offering themtrustworthy and safe contentsWe design and developtext and visionmachine learning models that runon thousands ofdifferent typesand slideshows)and user-generated commentshighly motivated andapplied scientist to

As a Senior Applied Scientist on our team, you will belatest deep learning techniques includinglarge language models fornatural language understanding and large vision models for image understanding

Required Qualifications:

• Bachelor's Degree in 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 Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in 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 experience developing machine learning models.
• 2+ years of experience as a tech lead or a similar role in developing machine learning models.
• 2+ years of experiencewith natural language processing.

Preferred Qualifications:

• Experience with machine learning model deployment and debugging.
• Experience with large language modelsandtransformers.
• Experience withcomputervision models, or visual content understanding.
• Experience with distributed big data processing.
• Experience in mentoring early in profession Applied Scientists.
• 2+ years of experience with statistical analysis and data visualization

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

• Conduct research and development incomputer vision,generative AI, knowledge distillation andmulti-modalitylearning to develop content moderation models.
• Own the problem end-to-end, from ideation to production, ensuring successful implementation.
• Leverage data analysis knowledge to clean, transform, analyze, integrate, and organize data to the levelrequiredformachine learningmodel development.
• Contribute to the definition of content moderation policies.
• Work withscience and engineeringteam toimproveexistingdata labeling techniques andmodeldesign.
• Mentor and coachless experiencedscientistson the best practicesin datapreparation, data labelingandmodeling.
• Perform documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Creates informal documentation and may share findings to promote innovation within groups or with other groups.
• Embody ourand