GPU / AI Power Performance SR Staff Engineer

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