Microsoft Applied Scientist Microsoft AI – PhD Internship Opportunities Redmond 

Taiwan, Taoyuan City 

382043260

As an Applied Scientist PhD intern in Monetization at Microsoft AI, our work is at the forefront of one of the fastest growing areas on the Internet—online advertising and intelligent monetization solutions. Our work powers products like Bing Ads, Copilot, and the broader Microsoft ecosystem, serving billions of ad impressions and generating terabytes of user interaction data every day. The rapid evolution of this space presents incredible opportunities and complex technical challenges that require cutting-edge solutions in machine learning, natural language processing, data mining, and large-scale optimization.

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Required Qualifications:

• Currently pursuing a Doctorate Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• Must have at least one additional quarter/semester of school remaining following the completion of the internship
• Candidate must be enrolled in a full time bachelor's, masters, MBA, or PhD program in area relevant for the role during the academic term immediately before their internship.

Other Requirements:

• Ability to submit an official or unofficial academic transcript as part of the evaluation process, if selected for interviews.

The base pay range for this internship is USD $6710.00 - $13270.00 per month. 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 $8760.00 - $14360.00 per month.

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

• Analyze and improve performance of advanced algorithms on large-scale datasets and cutting-edge research in machine intelligence and machine learning applications.
• Think through the product scenarios and goals, identify key challenges, then fit the scenario asks into Machine Learning (ML) tasks, design experimental process for iteration and optimization.
• Implement prototypes of scalable systems in AI applications.
• Gain an understanding of a broad area of research and applicable research techniques, as well as a basic knowledge of industry trends and share your knowledge with immediate team members.
• Prepare data to be used for analysis by reviewing criteria that reflect quality and technical constraints. Reviews data and suggests data to be included and excluded and be able to describe actions taken to address data quality problems.
• Assist with the development of usable datasets for modeling purposes and support the scaling of feature ideation and data preparation.
• Help take cleaned data and adapt for machine learning purposes, under the direction of a senior team member