Staff Platform System Architect, AI/ML, Silicon

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience in system architecture, software engineering, or AI/ML development.
• 5 years of experience in mobile SoC architecture, computer architecture, or embedded system design, with an emphasis on Software/Hardware co-design for AI/ML workloads.
• Experience in translating product requirements or user needs into technical system architecture specification and design.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  
• Experience optimizing software and systems for power, thermal, and memory footprint constraints.
• Experience with AI/ML model architectures, including Generative AI models (e.g., Transformers, LLMs, Diffusion Models).
• Knowledge of mobile SoC architectures (e.g., Arm-based SoCs), with experience in Tensor.
• Familiarity with on-device AI inference, runtime environments, and model adaptation techniques (e.g., quantization, pruning).
• Understanding of computer architecture principles, including CPU/GPU/NPU interactions, memory systems, and on-chip interconnects.

About the job

Be part of a 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.

As a Staff System Architect, as part of the Silicon Platform System Architecture team, you will enable and land Google's latest Generative AI (GenAI) technologies on Pixel phones, powered by the Tensor SoC. You will drive the future of on-device AI by leading Software/Hardware co-design efforts to unlock novel and compelling GenAI user cases that improve the Pixel user experience. You will be responsible for architecting and enabling high-performance, power-efficient GenAI solutions, working at the intersection of AI model understanding, latest mobile AI use cases, mobile SoC capabilities, and system-level optimization, all within the demanding power, thermal, and memory constraints of mobile devices.

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 $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Lead and advocate Software/Hardware co-design with hardware, software, and product teams to identify, define, and enable the GenAI-driven user experiences on Pixel.
• Architect end-to-end system solutions for deploying Generative AI models on Pixel, ensuring seamless integration and optimal utilization of the Tensor SoC.
• Collaborate with hardware architects to influence future Tensor SoC designs and capabilities, ensuring suitability for upcoming GenAI workloads and user experiences.
• Provide technical leadership and collaboration between AI researchers, model developers, Android engineers, hardware architects, and UX/product teams to deliver cohesive GenAI solutions.
• Translate GenAI research and product ideas into feasible on-device applications. Define system requirements and architectural pathways to bring these AI experiences to life.