Multimedia Machine Learning Silicon Architect, Devices and Services

architecture design.

• Familiarity in machine learning and image, video, display processing algorithms for mobile photography applications.

About the job

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 develop system architectures with hardware acceleration for Machine Learning (ML) in multimedia use cases. You will work with research, algorithm, product managers, hardware, software or System-on-a-Chip (SOC) architecture, and implementation teams to define the end-to-end Machine Learning (ML) acceleration solution, the solution space will include custom hardware and software, and the solution will have the entire technology stack considered. Overall, you will play a critical role in enabling Google-only on-device experiences to the users.

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 $127,000-$187,000 + 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 .

Responsibilities

• Analyze key Machine Learning (ML) workloads, related user's experience and identify hardware acceleration opportunities.
• Explore design space and map end-to-end user experience to hardware (HW) and software (SW) components on SoC.
• Design Machine Learning (ML) acceleration architecture with comprehensive architectural and quality analyses.
• Collaborate with algorithm owners to design hardware-oriented networks.
• Deliver comprehensive architecture specification and analyses.