Microsoft is hiring for the Applied Sciences Internship, a hands-on opportunity focused on machine learning, large-scale datasets, and scalable AI systems. This article explains the role’s core responsibilities in detail and clarifies the academic eligibility requirements. Read on to understand how responsibilities like prototyping, data preparation, experiment design, and supervised model adaptation come together in this internship.
Role and Responsibilities
This internship centers on practical applied-science work across algorithms, data, and prototype systems. Key responsibilities are interconnected and emphasize iteration, collaboration, and scalable solutions:
- Analyze and improve performance of advanced algorithms on large-scale datasets and machine learning applications — work focuses on measuring algorithm behavior on real datasets and driving performance improvements for production-relevant ML applications.
- Translate product scenarios into ML tasks, design experiments for iteration and optimization — responsibilities include converting product needs into concrete machine learning tasks and setting up experiments to iterate and optimize solutions.
- Implement prototypes of scalable AI systems — develop prototype implementations that demonstrate scalable approaches to the ML problems derived from product scenarios.
- Prepare and review data for analysis, address data quality issues — responsibilities cover preparing datasets for analytical use and tackling data quality concerns that affect modeling and evaluation.
- Assist development of usable datasets and support scaling of feature ideation and data preparation — support the creation of usable datasets and help scale processes for feature ideation and data preparation across projects.
- Adapt cleaned data for machine learning under senior supervision — after data cleaning, adapt datasets for ML model consumption while working under senior guidance.
- Learn and apply research techniques; share knowledge with team members — the role involves applying research methods to tasks and communicating findings with peers to contribute to team learning.
Eligibility and Internship Details
The internship is designed for students who are actively pursuing relevant undergraduate study and will remain enrolled after the internship. Eligibility and academic expectations are:
- Currently pursuing a Bachelor’s degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field — candidates must be enrolled in one of the specified technical disciplines or a closely related area.
- Must have at least 1 quarter/semester remaining after the internship — candidates are required to continue their academic program for at least one academic period following completion of the internship.
Together, these requirements ensure interns can engage in the full cycle of applied-science work—data preparation, experiment design, prototyping, and knowledge sharing—while receiving senior supervision and contributing to scalable ML solutions.
Conclusion
Microsoft’s Applied Sciences Internship emphasizes hands-on machine learning work: analyzing and improving algorithms on large-scale datasets, translating product scenarios into ML tasks, prototyping scalable AI systems, and preparing data for analysis under senior supervision. Eligible candidates must be pursuing a relevant Bachelor’s degree and have at least one quarter or semester remaining after the internship. This role offers structured exposure to applied research and scalable ML development.
