Research Intern - Cloud Efficiency & Reliability

1 Month ago • 1 Years + • Research & Development • $78,600 PA - $154,560 PA

About the job

Job Description

Microsoft offers a Research Internship focusing on Cloud Efficiency & Reliability. Interns will contribute to research projects improving cloud efficiency, reliability, and sustainability, leveraging AI/ML and hardware innovation. Responsibilities include optimizing GenAI/LLM inferencing, workload-aware resource placement, workload modeling, fault injection, and dependency graph mining for web-scale systems. The internship requires a PhD background in a relevant STEM field, research experience, and peer-reviewed publications. Interns will collaborate with researchers and product groups, presenting findings and contributing to a vibrant research community. The internship is typically 12 weeks long.
Must have:
  • PhD in Computer Science or related field
  • 1+ years research experience
  • Peer-reviewed publications
  • Systems research background
  • Experience with distributed systems
Good to have:
  • Experience with cloud infrastructure
  • Software development experience
  • Publications in top-tier conferences (OSDI, SOSP, etc.)
  • Proficient communication skills
  • Ability to work in cross-functional teams
Perks:
  • Industry-leading healthcare
  • Educational resources
  • Product and service discounts
  • Savings and investment plans
  • Maternity and paternity leave
  • Generous time off
  • Giving programs
  • Networking opportunities

Overview

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.

In the , we are leveraging our deep workload understanding and combining algorithmic research with Artificial Intelligence (AI)/Machine Learning (ML) techniques and hardware innovation to provide a step function improvement in cloud efficiency, reliability and sustainability. We closely collaborate with multiple research teams and product groups across the globe who bring a multitude of technical expertise in cloud systems, machine learning and software engineering. We disseminate our research both internally and externally through peer-reviewed scientific publications, open-source releases, blog posts, patents, and industry conferences.

 

For this position, you will have a background in Systems research and the motivation and ambition to apply this to production systems. Some of the research problems we are currently working on are: optimizing inferencing of Generative Artificial Intelligence (GenAI)/Large Language Models (LLMs), workload-aware placement of compute resources, holistic characterization and modelling of workloads, fault injection for improving workload reliability and mining dependency graphs for web-scale systems. 

Qualifications

Required Qualifications

  • 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.

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

  • Experience with distributed systems, cloud infrastructure and software development.
  • Proficient written and verbal communication skills. 
  • Able to work in a cross-functional and multi-disciplinary setting across research and product.
  • Published in one of the following venues: OSDI, SOSP, ASPLOS, NSDI, EuroSys, ATC, SoCC, MLSys, ICSE, FSE, WebConf, etc.

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: 

 

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

  •  

Responsibilities

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.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect
View Full Job Description
$78.6K - $154.6K/yr (Outscal est.)
$116.6K/yr avg.
Redmond, Washington, United States

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