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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 mission of the AI Frontiers Lab is to expand the pareto frontier of Artificial Intelligence (AI) capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. Some of our projects include work on Small Language Models (e.g. Phi, Orca), agentic AI systems (e.g. AutoGen, MagenticOne, OmniParser), new transformer architectures (e.g. Belief State Transformers) and optimizers for scalable Large Language Model (LLM) Training (e.g. Dion). Our ongoing research areas encompass but are not limited to: Reasoning method for LLMs and multimodal models; New model architectures and training methods; Action models for automating web and computer tasks; Orchestration and multi-agent systems: automated orchestration between multiple agents incorporating human feedback and oversight; Evaluation and Understanding of model and agent capabilities.
Job Responsibility:
Perform cutting-edge research in collaboration with other researchers, engineers, and product groups
Be a part of research breakthroughs in the field and will be given an opportunity to realize your ideas in products and services used worldwide
Embody our culture and values
Requirements:
Currently enrolled in a master’s or PhD program in Computer Science or a related STEM field
Demonstrable ability to define an ambitious, original research agenda
Experience publishing academic papers as a lead author or essential contributor in the field of Artificial Intelligence
Experience participating in a top conference in relevant research domain
Ability to collaborate, communicate effectively, and work as part of a multi-disciplinary team
Keen interest in real-world applications and impact
Experience in Machine Learning, Computer Vision and related fields
Research demonstrated by publications at the following conferences: NeurIPS, ICML, ICLR, ACL, NAACL, CVPR, COLT, ECCV, ICCV, EMNLP