Imaging and Multimedia System Architect - Silicon

Imaging and Multimedia System Architect – Silicon

Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
5 years of experience with computer architecture concepts, including microarchitecture, cache hierarchy, pipelining, and memory subsystems.
5 years of experience working on mobile System-on-a-Chip (SoCs).
3 years of experience in mobile SoC system architecture and subsystems including Camera ISP, ML, NPU, GPU, Video Codecs or Display.
3 years of experience in Android multimedia software development including drivers, HAL, framework and applications.

Collaborate with Google research, product management, SoC and IP architecture, and Pixel product teams to define the product roadmap for Camera, Imaging, and GenerativeAI user experiences powered by the Google Tensor SoCs.
Develop end-to-end system architecture and lead workstreams to enable new and emerging GenerativeAI and Computational Imaging use-cases, from concept through product launch.
Perform system architecture analysis for complex Imaging, Generative AI and Multimedia user experiences to identify performance and power bottlenecks and areas for optimizations in hardware and software.
Develop technical collaterals to influence architecture and design decisions on future Tensor SoCs.
Collaborate with multimedia IP architecture, system architecture and device software teams to build prototypes/production software across the Android camera, machine learning and multimedia stack to demonstrate feasibility of new and emerging use-cases on future Tensor SoCs.

Experience in collaborating with multiple teams/stakeholders across organization boundaries to launch new features and use-cases on mobile devices.
Experience with system architecture analysis for Imaging, Generative AI and Multimedia user experiences to identify performance and power bottlenecks and areas for optimization.
Experience with workload performance and power characterization, using tools such as Perfetto and Systrace on Android.
Experience with ML inference pipeline development and optimization on mobile devices.
Experience with GPU and DSP software development for imaging, computer vision and multimedia applications using programming languages such as OpenCL, Vulkan, CUDA, Halide and architecture specific C/C++ intrinsics.