| Microsoft Careers

Microsoft

Quick summary

Work type
On-site
Location
Redmond, WA
Posted
51 days ago

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Salary context

How this pay compares to similar roles

Similar $181k
$106k most similar roles pay here $248k

This listing doesn't post a salary. Most similar roles pay $155,000–$207,350.

Based on 238 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1103 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 985 roles with salary data.

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At a glance

TL;DR · | Microsoft Careers

Join Microsoft’s Systems Innovation initiative as a Research Intern to advance the efficiency of AI systems by exploring novel designs and optimizations across models, frameworks, cloud infrastructure, and hardware. This applied research role involves collaborating with global teams to drive mid- and long-term product innovations through academic publications, open-source releases, patents, blog posts, and industry conferences. Day-to-day responsibilities include applying deep technical expertise in areas such as deep learning, model compression, GPU architecture, and accelerator design to create efficient computational kernels for large-scale production systems. Candidates should possess advanced C++ programming skills, proficiency with GPU programming frameworks like CUDA or ROCm, and a strong background in parallel computing and algorithm optimization. This role requires an entrepreneurial mindset and the ability to move fast while tackling complex challenges in AI system efficiency.

What you'll do

  • Develop novel designs and optimizations for AI systems across the entire AI stack.
  • Explore and implement efficient computational kernels in large-scale production systems.
  • Collaborate on advancing efficiency of AI models, frameworks, cloud infrastructure, and hardware.
  • Apply deep technical expertise to solve complex challenges in computing and machine learning.
  • Publish research findings through academic publications, open-source releases, patents, and conferences.

What we're looking for

  • Currently enrolled in a PhD program in Computer Science, Software Engineering, Electrical Engineering, or related STEM field.
  • Background in deep learning, model compression, GPU architecture, accelerator design, machine learning, or systems research.
  • Proficient understanding of GPU architecture, memory hierarchies, parallel computing, and algorithm optimization.
  • Hands-on experience with GPU programming, performance profiling, and optimization tools.
  • Proficient knowledge of CUDA, ROCm, Triton, PTX, CUTLASS, or similar GPU programming frameworks.
  • Advanced C++ programming skills.

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