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GPU/AI Power Performance Staff Engineer

Qualcomm
September 04, 2026
Full-time
On-site
Bengaluru, Karnataka, India
ASIC Design Jobs, Level - Senior

Job Title

GPU/AI Power Performance Staff Engineer

Role Summary

Senior engineering role focused on GPU power and performance analysis for AI workloads. The role partners with hardware, software, and machine-learning teams to model power, identify bottlenecks, and recommend architectural or algorithmic optimizations that inform GPU roadmap decisions.

Experience Level

Senior (Staff). This is a senior engineering position with multi-year experience expectations; see Education Requirements for formal degree and experience guidance.

Responsibilities

Primary responsibilities include modeling, analysis, and cross-functional optimization for GPU power and performance:

  • Develop and maintain GPU power models and estimators for diverse AI workloads.
  • Analyze GPU architecture and microarchitecture for performance and power optimization opportunities.
  • Profile and correlate AI workload characteristics with power behavior across GPU generations.
  • Collaborate with hardware, software, and ML teams to locate power bottlenecks and propose fixes.
  • Contribute data-driven trade-off studies and influence GPU roadmap and architectural decisions.
  • Support validation and verification of power-optimization changes across tools and simulation environments.

Requirements

Key technical requirements. Education and degree/years guidance are summarized separately under Education Requirements.

Must-have:

  • Experience with ASIC design and verification and practical exposure to low-power ASIC optimization techniques.
  • Practical experience in power modeling, estimation, or power analysis for GPUs or other accelerators.
  • Programming skills in C/C++ and scripting (Python preferred).
  • Familiarity with RTL (Verilog/SystemVerilog) and assembly-level understanding related to microarchitecture.

Nice-to-have:

  • Experience with advanced CPU/GPU architecture or microarchitecture design and trade-off analysis.
  • Experience with ML frameworks (TensorFlow, PyTorch) and profiling ML workloads.
  • Familiarity with industry power tools (e.g., PrimeTime PX, PowerArtist) and graphics APIs (Vulkan, DirectX, OpenGL, OpenCL, CUDA).
  • Experience with GPU driver and compiler development and performance tuning.

Education Requirements

Degrees and equivalent experience: Bachelor's, Master's, or PhD in Engineering, Computer Science, Computer Engineering, Electrical Engineering, Information Systems, or a related technical field are referenced. The posting specifies degree-to-experience mappings: Bachelor's +6 years of relevant Systems Engineering experience OR Master's +5 years OR PhD +4 years. The posting also references Master's or PhD (or equivalent) in related fields and lists domain-specific expectations such as ASIC design and low-power optimization; equivalent practical experience is accepted where noted.


About the Company

Company: Qualcomm

Headquarters: San Diego, California, United States

Qualcomm is a global leader in semiconductor and telecommunications equipment, specializing in mobile technologies and innovations. Known for its Adreno GPUs, the company provides solutions enabling advancements in mobile gaming, AI, VR/AR, and autonomous driving. Qualcomm's cutting-edge technology and commitment to high-performance, power-efficient designs drive the evolution of mobile graphics and connectivity worldwide.

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Date Posted: 2026-09-03