GPU/AI Power Performance Staff Engineer
Qualcomm · Bengaluru · 2+ yrs experience · Posted 2026-05-09
Tech stack: C, C++, Python
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About the role
Qualcomm India Private Limited
Engineering Group, Engineering Group > Systems Engineering
Responsibilities: - 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
Qualifications: - Master's or PhD degree or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or related field..
- 2+ years of experience with ASIC design and verification
- 2+ years of experience with low-power ASIC optimization
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
- 5+ years of experience with advanced CPU/GPU architecture/microarchitecture design development
- 5+ years of experience with low-power ASIC design techniques
- Experience in Python, C++, and ML frameworks (e.g., TensorFlow, PyTorch)
- 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
- C/C++ Programming Language, Scripting (Python/Perl), Assembly, Verilog/SystemVerilo
Qualifications
- Master's or PhD degree or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or related field..
- 2+ years of experience with ASIC design and verification
- 2+ years of experience with low-power ASIC optimization
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
- 5+ years of experience with advanced CPU/GPU architecture/microarchitecture design development
- 5+ years of experience with low-power ASIC design techniques
- Experience in Python, C++, and ML frameworks (e.g., TensorFlow, PyTorch)
- 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
- C/C++ Programming Language, Scripting (Python/Perl), Assembly, Verilog/SystemVerilo
Responsibilities
- 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