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Research Intern - AI-driven System and Database Design
$5k - $10k
Redmond, United States
Job description

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.

As a Research Intern at Microsoft Research, you will be at the forefront of developing and implementing cutting-edge Artificial Intelligence (AI)-driven AI infrastructure. This role is ideal for candidates who are passionate about AI software and hardware development. You will collaborate with a team of world-class researchers and engineers in Vancouver, Canada, and Redmond, Washington to create the next generation of AI infrastructure that enhances the efficiency and effectiveness of AI.

What we expect from you

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. As a Research Intern for this position, you will:

  • Development and Implementation: Design and develop AI-driven AI infrastructure. Implement prototypes and conduct simulations to test and validate them.
  • Research and Analysis: Conduct thorough research on emerging trends in AI software and hardware infrastructure.
  • Collaboration: Work closely with cross-functional teams, including hardware engineers, software developers, and data scientists, to integrate your ideas with existing and future AI projects.
  • Documentation and Reporting: Prepare detailed documentation of simulations, methodologies, and findings. Present results and insights to team members and stakeholders.
  • Innovation and Problem-Solving: Identify challenges and bottlenecks in AI infrastructure and propose innovative solutions.