Research Intern - OneDrive and SharePoint (Summer 2026) at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Mar, 26

Salary

13270.0

Posted On

10 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Deep Learning, Python, PyTorch, Large Language Models, Reinforcement Learning, Conversational AI, Data Science, Statistics, User Studies, Content Management, Evaluation Metrics, Algorithm Development, Research Publications, Collaborative Skills, Problem Solving

Industry

Software Development

Description

Overview Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. The OneDrive and SharePoint (ODSP) Applied Science team is an interdisciplinary group of researchers and engineers driving Artificial Intelligence (AI) innovation to transform how users remember, reason, act on their content and collaborate with others via Microsoft products. We tackle high-impact challenges to deliver tangible customer and business value by performing cutting-edge research and translating it into technologies that empower millions of users. We are looking to hire several PhD candidates for 12-week summer internships based in Redmond, WA. Research Interns will be expected to investigate, propose, implement, and evaluate new approaches within the broader areas of large language models (LLMs), Multimodal AI, Reinforcement Learning, Conversational AI, and AI Agents. As a Research Intern you will partner with product and engineering teams, to invent and deliver the future of content and collaboration at Microsoft. You will be expected to present results internally at the end of the internship and to write up their work for publication at leading academic venues (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR, etc.). Research Internships offer an opportunity to work in a supportive, inclusive and collaborative environment. You’ll join a culture that values growth mindset and teamwork, providing you with opportunities to be mentored by world-class AI researchers and engineers, as well as other learning and career development resources as you help shape the future of content and collaboration in ODSP. Responsibilities Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world’s best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. Additional Responsibilities Conduct experiments and develop novel AI models and algorithms to address complex ODSP scenarios (e.g., intelligent document understanding, search/RAG, recommendation, generative experiences, proactive knowledge mining). Design rigorous evaluation metrics, methodologies, and validation experiments to measure performance and quality of devised AI solutions and agentic AI workflows. Conduct user studies to gather qualitative and quantitative insights, ensuring solutions align with user needs and improve real-world experience. Build datasets (including leveraging privacy-preserving synthetic data techniques) to fine tune and benchmark models for ODSP applications. Deliver models and algorithms for content understanding, enrichment, and use at scale, across a range of different modalities, including text, images, and video. Apply your in-depth knowledge, problem-solving skills, and drive to solve new challenges in the field and realize your ideas in products used worldwide. Present research findings and propose ideas in team discussions; share results through documentation and presentations and contribute to research publications. Embody Microsoft culture and values. Qualifications Required Qualifications Currently enrolled in a PhD program in Computer Science, Electrical/Computer Engineering, Data Science, Statistics, or related fields. Other Requirements Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship. In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter. Preferred Qualifications Demonstrated foundation in machine learning and artificial intelligence. Hands-on experience with modern deep learning techniques (e.g., transformer models, large language models). Practical Python coding experience with PyTorch or similar frameworks. Ability to prototype and implement algorithms efficiently. Proficient analytical, problem solving, communication, and collaborative skills. Able to formulate hypotheses, drive experiments, and work effectively in a collaborative environment. Demonstrated research impact through publications or projects in relevant AI domains (e.g., natural language processing, information retrieval, computer vision, multimodal AI, knowledge mining). A track record of applying scientific methods to real-world problems is a plus. Familiarity with LLM training or fine-tuning, particularly using reinforcement learning techniques or AI agent orchestrators. Experience working with large-scale datasets, enterprise content, or content management systems. Experience with privacy-preserving evaluation methods or synthetic data generation is highly desirable. The base pay range for this internship is USD $6,710 - $13,270 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 $8,760 - $14,360 per month. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Research Interns will investigate, propose, implement, and evaluate new approaches in AI, collaborating with product and engineering teams. They are expected to present results and contribute to research publications.