Graphics/AI Performance Engineer
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 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. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.Preferred Minimum Qualifications: 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/SystemVerilog
