Microsoft Senior Applied Scientist 

United States, Washington 

883820597

As a Senior Applied Scientist on our team, you will be using the latest deep learning techniques including generative AI, large language models for natural language understanding and large vision models for image understanding.

This role is available in

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 experience with natural language processing.

Preferred Qualifications:

• Experience with machine learning model deployment and debugging.
• Experience with large language models and transformers.
• Experience with computer vision 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:Microsoft will accept applications for the role until February 3, 2025.

• Conduct research and development in computer vision, generative AI, knowledge distillation and multi-modality learning 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 level required for machine learning model development.
• Contribute to the definition of content moderation policies.
• Work with science and engineering team to improve existing data labeling techniques and model design.
• Mentor and coach less experienced scientists on the best practices in data preparation, data labeling and modeling.
• 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 our and