About the job

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

As a Senior Graphics Processing Unit (GPU) Silicon Engineer in the Google Silicon team, you will be at the forefront of defining how our custom-designed hardware interacts with the entire software stack. You will drive the architecture and implementation of kernel-mode and user-mode drivers that power everything from high-end mobile graphics. You aren't just writing code, you are bridging the gap between hardware intent and software execution.

Responsibilities

• Design, implement, and maintain GPU drivers (Kernel and User mode) for custom Google Silicon.

• Lead the 'first-light' activities for new GPU IP on pre-silicon (emulation/FPGA) and post-silicon platforms.

• Profile and optimize the driver stack to eliminate bottlenecks, reduce overhead, and improve power efficiency.

• Implement and support industry-standard Application Programming Interfaces (APIs) such as Vulkan, OpenCL, and potentially proprietary compute extensions for Machine Learning/Artificial Intelligence (ML/AI).

• Partner closely with GPU Architects, Register-Transfer Level (RTL) Designers, and Operating System (OS) teams (Android/Linux) to influence future hardware features and software interfaces.

Minimum qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.

• 5 years of experience in device driver development (e.g., Linux/Android Kernel or RTOS).

• Experience in GPU architectures (e.g., pipelines, memory hierarchies, and command submission).

• Experience with graphics or compute APIs (e.g., Vulkan, OpenGL ES, or OpenCL).

Preferred qualifications

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.

• 8 years of experience with GPU Compiler interactions or Low Level Virtual Machines (LLVM)-based backends or GPU performance improvement.

• Experience with pre-silicon emulation environments (Palladium, Zebu, or Veloce) and developing and debugging native code on Android.

• Knowledge of Memory Management Units (IOMMU/GMMU), power management, and interrupt handling.

• Familiarity with AI/ML frameworks (e.g., Tensor Flow, Py Torch) and how they leverage GPU kernels.

• Track record of shipping production-quality drivers for high-volume consumer electronics.