Research Intern, Hardware Software Codesign

Microsoft

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Posted
67 days ago

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Similar $181k
$131k most similar roles pay here $228k

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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 694 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 636 roles with salary data.

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TL;DR · Research Intern, Hardware Software Codesign

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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 working closely with global teams to drive mid- and long-term product innovations through academic publications, open-source releases, patents, and industry conferences. Day-to-day responsibilities include applying deep technical expertise in areas like 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 such as CUDA or ROCm, and a strong entrepreneurial mindset to tackle complex challenges in AI system efficiency.

Skills

CUDA GPU ROCm Triton PTX CUTLASS C++ Parallel Computing Algorithm Optimization Performance Profiling GPU Programming Memory Hierarchies

What you'll do

  • Conduct research to advance efficiency across AI systems by exploring novel designs.
  • Develop and optimize computational kernels for large-scale production systems.
  • Collaborate on mid- and long-term product innovations within the AI stack.
  • Publish findings through academic publications, open-source releases, patents, and conferences.
  • Work with GPU architecture, memory hierarchies, parallel computing, and algorithm optimization.
  • Utilize GPU programming frameworks like CUDA, ROCm, Triton for performance profiling.
  • Implement efficient solutions to complex challenges in computing and AI systems.

What we're looking for

  • Currently enrolled in a PhD program in Computer Science, Software Engineering, Electrical Engineering, or related STEM field.
  • Strong background in deep learning, model compression, GPU architecture, and accelerator design.
  • Proficient understanding of GPU memory hierarchies, parallel computing, and algorithm optimization.
  • Hands-on experience with GPU programming and performance profiling tools.
  • Advanced skills in CUDA, ROCm, Triton, PTX, CUTLASS, or similar GPU programming frameworks.
  • Demonstrated ability to solve complex technical problems and implement scalable computational kernels.

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