GPU / AI Power Performance SR Staff Engineer

Job description

**General Summary:** - **Job Description** - 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 **Minimum 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 **Minimum Qualifications:** - Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience - ORMaster's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience - ORPhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience **Preferred Qualifications:** - 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 **Skills:** C/C++ Programming Language, Scripting (Python/Perl), Assembly, Verilog/SystemVerilo