Research Intern - Azure Cloud Server Performance

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Date posted

Dec 27, 2024

Job number

1798099

Work site

Up to 50% work from home

Travel

None

Role type

Individual Contributor

Profession

Research, Applied, & Data Sciences

Discipline

Applied Sciences

Employment type

Internship

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.

We are building new systems to optimize the millions of server nodes underlying the Microsoft Azure cloud. You will be part of a dynamic and collaborative team chartered to understand and improve how hardware and software ingredients come together to form our Azure VM products. Our work includes optimizing fleet performance, competitive comparisons, developing tools that leverage AI, and providing input to hardware selection.

Required Qualifications

• Currently enrolled in a PhD program in Computer Science, Computer Engineering, or a related STEM field.
• At least 1 year or project's worth of experience working with CPU performance counters, such as with EMON, Linux perf, or a similar method of working directly with microarchitectural performance counters in a hardware system, simulation, or emulation environment.

Other Requirements

• 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. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.

Preferred Qualifications

• Ability to independently drive research ideas, plus collaborate with other researchers and development teams.
• Research publications on microarchitectural techniques, performance benchmarking, or cloud workload analysis.
• At least 1 year of experience working with a microarchitectural simulator, such as gem5 or Simplescalar.

The base pay range for this internship is USD $6,550 - $12,880 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,480 - $13,920 per month.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay

Microsoft accepts applications and processes offers for these roles on an ongoing basis.

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.

In this role, you will work to understand and classify cloud workload behavior. You will develop usage models based on hardware telemetry and use the data collected to influence benchmark selection and which hardware we put into next generation cloud systems. You will also gain insight into what workloads matter in a hyperscale public cloud and how platform and hardware design choices affect cloud customer experience and operational efficiency. The knowledge you gain will help you create the future of at-scale computing.