Google is hiring: Multimedia Machine Learning Silicon Architect, Devices and Ser

Minimum qualifications:

1. Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
2. 3 years of experience in machine learning or multimedia technologies.
3. Experience in architecture or silicon engineering such as computer architecture, Digital Signal Processor (DSP) circuits, Very-Large-Scale Integration (VLSI), Register-Transfer Level (RTL).

Preferred qualifications:

1. Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
2. 5 years of relevant experience in the SoC or Hardware industry.
3. Experience in mobile cameras, computational photography techniques, depth sensing cameras and others.
4. Experience in Machine Learning (ML) hardware architecture and computer hardware architecture design.
5. Familiarity in machine learning and image, video, display processing algorithms for mobile photography applications.

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, considering custom hardware and software, and the entire technology stack. Overall, you will play a critical role in enabling Google-only on-device experiences to the users.

+ Analyze key Machine Learning (ML) workloads, related user experiences, 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 specifications and analyses.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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