Research Intern - OneDrive and SharePoint (Summer 2026)

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. 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. Currently enrolled in a PhD program in Computer Science, Electrical/Computer Engineering, Data Science, Statistics, or related fields. 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. 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.

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