Microsoft is hiring a Research Sciences Intern to work at the intersection of large-scale machine intelligence and systems engineering. This article details the role’s core responsibilities — from analyzing advanced algorithms on big data to moving prototypes into production — and outlines the doctorate-level candidate requirements and collaboration expectations for successful applicants.
Role Responsibilities in Research and Systems
This internship centers on rigorous research and practical system implementation across AI and machine learning domains.
- Performance analysis and improvement: Analyze and improve performance of advanced algorithms on large-scale datasets and machine intelligence/ML applications, focusing on measurable gains in scalability and effectiveness.
- Scalable prototypes: Implement prototypes of scalable systems in AI applications and collaborate with team members to take these systems from prototyping to production, ensuring prototypes are designed with production integration in mind.
- Real-world solutions: Develop solutions for large-scale real-world problems by applying a combination of algorithmic advances and system-level designs to meet practical deployment needs.
- Research and tool development: Research new tools, technologies and methods and contribute specialized knowledge to support research planning; this includes authoring white papers and contributing to internal research documentation.
- Technology transfer and dissemination: Assist in technology transfer, participate in standards organizations, file patents, and support the movement of research outcomes into broader use and formal channels.
- Internal support and consultation: Develop and maintain internal tools/services or consult for product/business groups to help translate research prototypes into usable components for other teams.
Candidate Requirements and Collaboration Expectations
This role requires doctoral-level training combined with applied experience and strong collaborative skills.
- Academic standing: Currently pursuing a Doctorate in a relevant field, with at least one additional quarter or semester of school remaining after the internship period.
- Technical experience: Experience designing scalable data systems and applying LLMs and machine learning techniques to large-scale data applications (or integrating both approaches), demonstrating capacity to handle both model and system-level challenges.
- Research leadership: Demonstrated ability to develop original research agendas, contributing novel directions that align research outcomes with practical system needs.
- Cross-functional collaboration: Ability to collaborate effectively with researchers and product development teams, supported by strong interpersonal and cross-group/cross-cultural collaboration skills to navigate diverse stakeholders.
- Creative problem-solving: Ability to think unconventionally to derive creative and innovative solutions when standard approaches do not suffice.
Conclusion
This Research Sciences Intern role at Microsoft combines rigorous research with practical system building: analyzing algorithms on large-scale datasets, prototyping scalable AI applications, and guiding technology transfer into production and standards. Candidates must be doctoral students with relevant experience in scalable data systems, LLMs and ML, strong collaboration and creative problem-solving. Consider this opportunity if you meet these focused requirements.
