Research Intern - OneDrive and SharePoint

• 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

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

A track record of applying scientific methods to real-world problems is a plus