Overview
Join us to push the frontier of AI efficiency and agentic systems. At M365 Research, we work at the intersection of cutting-edge research and product impact at global scale. We partner with research and product teams across Microsoft to deliver innovations that power experiences for hundreds of millions of users worldwide. Our work also spans academic publications, open-source projects, patents, and leading industry conferences.
We're seeking research interns passionate about advancing the state of the art in AI. You'll work on projects that combine deep technical innovation with real-world impact, contributing to breakthroughs that shape next-generation experiences for millions of users.
What you'll do
• Build Smarter LLM Agents: Design and develop next‑generation agents that go beyond simple task execution. You'll leverage memory, dynamic tool use, reinforcement learning, and multi‑agent collaboration to create robust, adaptive ecosystems that deliver real value in complex workflows.
• Drive Efficiency in LLM Applications: Pioneer innovations to make LLM applications faster, more scalable, and cost-effective. Your work will span context engineering, adaptive inference, and system level optimization across frameworks, reducing latency and resource usage without sacrificing quality.
What we're looking for
The ideal candidate has a strong foundation in machine learning and natural language processing, with experience in LLM applications or agent frameworks. You should bring curiosity, technical depth, and the ambition to apply research in practical settings, delivering innovations that move AI forward.
Responsibilities
• Participate in a 12-week internship program designed to provide hands-on experience and professional development. (Intern opportunities are available year-round, though they typically begin in the summer.)
• Collaborate with mentors, fellow interns, and researchers to conduct cutting-edge research and develop efficient AI algorithms and models.
• Engage in various research areas to broaden your expertise.
• Present your findings and actively contribute to the vibrant life of the research community.
Qualifications
Required Qualifications
• Currently enrolled in a PhD program in Computer Science, Mathematics, or a related STEM field.
• Minimum 1 year of research experience, including peer reviewed publications and software development.
We recommend submitting two reference letters to strengthen your application. After you submit your application, a request for letters may be sent to your listed references on your behalf. Note that reference letters cannot be requested until after your application is submitted, and they may not be automatically requested for all candidates. We suggest notifying your referees in advance so they are prepared.
Preferred Qualifications
• Experience in building LLM agents and working with agentic frameworks, and/or in optimizing LLM-based applications for efficiency and scalability
• Strong research background with publications in top conferences/journals in one or more areas: natural language processing, machine learning, optimization, or statistics.
• Strong programming skills, preferable in Python.
• Excellent written and verbal communication skills.
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.