Minimum qualifications:
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.
Preferred qualifications:
- 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.
Be part of a diverse 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.
In this role, you will leverage your expertise in Camera and Imaging, Machine Learning, and Multimedia system architecture and design to enable new and emerging user experiences for future Google Tensor SoC-based Pixel devices, powered by the most advanced Google research in Computational Photography and Generative AI.
Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.
The US base salary range for this full-time position is $150,000-$223,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.
- 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.