Research Intern - AI HW/SW Co-design

1 Month ago • 1 Years + • Artificial Intelligence • Research & Development • $65,520 PA - $128,880 PA

Job Summary

Job Description

This Research Internship at Microsoft's Azure Hardware Systems & Infrastructure (AHSI) organization focuses on AI HW/SW co-design. Interns will collaborate with researchers and engineers on projects exploring the intersection of AI and hardware/software co-design, optimizing AI model performance and power. Responsibilities include benchmarking neural network architectures, performance analysis, developing co-design techniques, prototyping optimizations, and contributing to research publications. The internship requires experience with deep learning hardware architectures and programming languages like Python, C++, or CUDA. Familiarity with AI frameworks and hardware description languages (HDLs) is preferred.
Must have:
  • Master's or PhD in relevant field
  • 1+ years deep learning hardware experience
  • Understanding of Neural Networks
  • Proficiency in Python/C++/CUDA
Good to have:
  • Experience with HDLs (VHDL/Verilog)
  • AI framework experience (TensorFlow/PyTorch/Caffe)
  • Knowledge of machine learning accelerators
  • Previous research experience

Job Details

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.

Join our Strategic Planning and Architecture (SPARC) team within Microsoft’s Azure Hardware Systems & Infrastructure (AHSI) organization and be a part of the organization behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission.  The SPARC organization manages Azure’s hardware roadmap from architecture concept through production for all of Microsoft’s current and future cloud deployments. 

 

AI System Architecture (ASA) within SPARC has the mission to co-design system architecture of Azure AI cloud keeping in pace with evolving landscape of Neural Network models. We are seeking a motivated AI HW/SW Co-Design Research Intern to join our team. As a Research Intern, you will have the opportunity to work on exciting projects that explore the intersection of AI and hardware/software co-design. You will collaborate with experienced researchers and engineers, gaining valuable hands-on experience in this dynamic field and explore ways to push the boundaries on AI model performance/power optimization on latest hardware/system architectures.

Qualifications

Required Qualifications

  • Currently pursuing a master's or PhD degree in Electrical Engineering, Computer Engineering or Computer Science.
  • At least 1 year experience on working with deep learning hardware architectures.

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 understand prevailing Neural Network Architectures.
  • Proficient understanding of AI algorithms and hardware architectures.
  • Experience with hardware description languages (HDLs) such as VHDL or Verilog.
  • Proficiency in programming languages such as Python, C++, or CUDA.
  • Familiarity with AI frameworks such as TensorFlow, PyTorch, or Caffe.
  • Knowledge of machine learning accelerators and hardware/software co-design methodologies.
  • Previous research experience or internships in related fields.

Applied Sciences IC2 - The base pay range for this internship is USD $5,460 -$10,680 per month.

 

There is a different range applicable to specific work locations, with the San Francisco Bay area and New York City Metropolitan area, and the base pay range for this role in those locations is USD $7,040 -$11,640 per month.


Applied Sciences IC3 - 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.

 

 

#AHSI #MSFTNSBE25

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.

Additional Responsibilities

  • Benchmark prevailing Neural Network architectures to understand Hardware/system characteristics.
  • Participate in performance analysis and optimization of AI workloads.
  • Come up with AI algorithms, system or hardware architecture innovations to drive efficiencies.
  • Assist in conducting research on AI hardware/software co-design methodologies.
  • Develop and implement co-design techniques to optimize AI performance.
  • Prototype the ideas to demonstrate the optimizations.
  • Write white papers and research publications.

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