Staff CAD Engineer, Silicon Design Environment, Cloud
Listed on 2026-08-10
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Engineering
Systems Engineer, Hardware Engineer, AI Engineer (Applied/Software), Test Engineer
Staff Cad Engineer, Silicon Design Environment
In this role, you'll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You'll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Staff Cad Engineer, Silicon Design Environment, you collaborate closely with domain experts across the silicon development spectrum and leverage your experience to deliver the development environment that enables building the chips powering the next generation of Google Cloud systems.
Responsibilities:
- Leverage the understanding of the phases of silicon development to flesh out the architecture and lead development and deployment of the overall CI2 design environment as a coherent system composed of first-party and third-party tools, industry-standard and Google-specific APIs/data formats and the scalable design flows.
- Collaborate with technical leaders across CI2 sites to identify opportunities for evolutionary and revolutionary tooling and methodology changes to enable convergence on a shared design environment.
- Engage with other Alphabet teams, Deep Mind, and Core teams to ensure CI2 stays at the forefront of advanced silicon development.
- Ensure developed technologies optimize for project iteration speed while achieving the planned power, performance, cost, and quality metrics.
- Partner with other members of the tools and methodologies team to apply procedural and AI-first approaches to improve efficiency.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits
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