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GPU/AI Power Performance Staff Engineer

Qualcomm·Bengaluru

Pay not stated6–11 yrsFull-time
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About the role

Analyze and evaluate GPU architecture/microarchitecture for performance and power optimizations Collaborate with hardware, software, and ML teams to identify power bottlenecks and propose architectural or algorithmic optimizations Analyze AI workload characteristics and correlate them with power behavior across different GPU generations

What you'll do

  • Develop and maintain GPU power modeling and estimation for diverse AI workloads
  • Analyze and evaluate GPU architecture/microarchitecture for performance and power optimizations
  • Collaborate with hardware, software, and ML teams to identify power bottlenecks and propose architectural or algorithmic optimizations
  • Analyze AI workload characteristics and correlate them with power behavior across different GPU generations
  • Contribute to architectural trade-off studies and influence GPU roadmap decisions with data-driven insights

What you need

  • 6–11 yrs of experience
  • C++
  • Python
  • C
  • Verilog
  • Perl
  • VLSI
  • PhD or B.Tech or B.E. or B.Sc or BCA or M.Tech

Good to have

  • TensorFlow
  • PyTorch
  • Machine learning

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