Microsoft is looking to advance Artificial Intelligence (AI) and Systems by pioneering advancements in AI agents that can reason, adapt, and act in complex environments. This research aims to transfer innovative technologies into Microsoft products, establish leadership in technical domains, and enhance community engagement.
Requirements
- Experience in machine learning, natural language processing, or related AI areas (e.g., LLMs, AI agents, Reasoning).
- Hands-on experience with one or more topics: large language model fine-tuning, reinforcement learning, prompt engineering, agent memory architectures, planning and reasoning modules, or multi-agent system design and implementation.
- Research contributions demonstrated through publications in top venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, IJCAI, KDD or related conferences.
Responsibilities
- adapting large language models (LLMs) to new domains
- designing LLM-based agents for workflow automation and advanced tool usage
- developing advanced agent memory architectures for long-term reasoning and context retention
- exploring multi-agent collaboration and coordination
- enhancing agents’ ability to plan, reflect, and self-improve through feedback
- conducting research and authoring peer-reviewed publications
- collaborate with multiple research teams and product groups across the globe
Other
- Currently enrolled or accepted in a PhD program in Computer Science, Software Engineering, Electrical Engineering, or a related STEM field.
- At least 1 year of experience in conducting research and authoring peer-reviewed publications.
- 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.
- Strong written and verbal communication skills.
- Ability to collaborate effectively in cross-functional, multi-disciplinary teams across research and product groups.
