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GPU Power Systems Engineer

LinkedIn Qualcomm San Diego, CA
Not Applicable Posted April 17, 2026 Job link
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Requirements
  • GPU power modeling and estimation for projection and correlation
  • Experience with scripting in Python or Perl.
  • 5+ years of experience with low-power ASIC optimization
  • PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Preferred Skills
  • Knowledge of Graphics architecture is a plus
  • Master's or PhD degree or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or related field.
  • 8+ years of experience with advanced CPU/GPU architecture/microarchitecture design development
  • 8+ years of experience with VLSI design and verification
  • 8+ years of experience with low-power ASIC design techniques
  • Experience with industry tools such as PrimeTime PX and Power Artist
  • Experience with Vulkan, DirectX3D, OpenGL, OpenCL, or Cuda development
  • Experience with GPU driver and compiler development
  • Skills: C/C++ Programming Language, Scripting (Python/Perl), Assembly, Verilog/SystemVerilog, Design Verification
Education
  • (Not required) – GPU power modeling and estimation for projection and correlation
  • (Not required) – Bachelor's degree or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or related field.
  • (Not required) – Master's or PhD degree or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or related field.
  • (Not required) – Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
  • (Not required) – OR
  • (Not required) – Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
  • (Not required) – PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.