GPU Architect, Silicon
Description For GPU Architect, Silicon
Google is seeking a GPU Architect to join their hardware team, focusing on developing custom silicon solutions for their direct-to-consumer products. This role combines cutting-edge GPU architecture with Google's innovative hardware initiatives, specifically working on the Tensor SoC platform.
The position requires a strong background in computer architecture, with expertise in GPU workload analysis and optimization. You'll be working at the intersection of hardware and software, collaborating with various teams including Machine Learning, GPU Software, and Android to create efficient and powerful computing solutions.
As a GPU Architect, you'll be responsible for defining GPU cores, proposing architectural improvements, and enhancing the overall performance of Google's Tensor SoC. This role offers the opportunity to directly impact millions of users worldwide through Google's hardware products.
The ideal candidate should have a solid foundation in computer architecture concepts, experience with GPU workloads, and proficiency in programming languages like C++ and Python. Knowledge of graphics APIs (Vulkan, OpenGL), Android OS, and ARM-based architecture would be particularly valuable.
This position offers the chance to work with Google's diverse team that pushes boundaries in hardware development. You'll be part of a company that values innovation, inclusion, and making technology more accessible to everyone. The role combines technical expertise with creative problem-solving to develop the next generation of Google's hardware experiences.
Responsibilities For GPU Architect, Silicon
- Define Graphics Processing Unit (GPU) cores for the Tensor SoC based on GPU workload analysis
- Propose architectural features/requirements for GPU to better integrate GPU with Tensor SoC to improve overall performance
- Work with Google Machine Learning, GPU Software, Android and device teams to bring engaging experiences leveraging GPUs to Google
- Enhance the overall Tensor SoC and software stack for GPU workloads
Requirements For GPU Architect, Silicon
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience
- Experience in architecture performance analysis, tools, or simulators using C++ and Python or similar
- Experience in using computer architecture concepts, such as pipelining, caches, virtual memory
- Master's degree or PhD in Computer Science, Electrical Engineering preferred
- Experience developing and analyzing workloads for GPUs preferred
- Experience with developing optimizing compilers preferred
- Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware preferred
- Knowledge of ARM-based system architecture concepts preferred
Benefits For GPU Architect, Silicon
- Equal opportunity employer
- Accommodation for disabilities
- Diverse and inclusive workplace
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