From Google's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
In this role, you’ll work to shape the future of AI/ML hardware acceleration.
In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive 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.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving team behind Google's groundbreaking innovations, empowering the development of our AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Work with a group of architecture and silicon engineers to develop next-generation DFT/DFX features for large-scale SoCs.
Design and implement software and hardware validation solutions for advanced testing, including logic BIST (LBIST), memory BIST (MBIST), and Scan compression.
Research, develop, and integrate machine learning or semi-analytical models to solve complex DFT challenges.
Triage, debug, and resolve high-priority post-silicon yield and structural failures by driving advanced failure analysis (FA) and volume diagnostics.
Write and review technical specifications for SoC testability and partner with EDA vendors.
PhD degree in Electronics and Communication Engineering, Electrical Engineering, Computer Engineering or related technical field, or equivalent practical experience.
Experience in programming languages (e.g., C++, Python, Verilog), Synopsys, Cadence tools.
2 years of experience in Silicon Engineering post PhD.
Experience with Electronic Design Automation (EDA) tools in design, verification, DFT and implementation.
Design for Test (DFT) knowledge (Boundary Scan, ATPG, MBIST).
PhD degree in Electronics and Communication Engineering, Electrical Engineering, Computer Engineering or related technical field, or equivalent practical experience.
Experience in programming languages (e.g., C++, Python, Verilog), Synopsys, Cadence tools.
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Hi [Name], I just applied for the Silicon DFT Engineer, PhD, Google Cloud role at Google. My background in [your most relevant experience] lines up well with what the team is looking for. Would you be open to a quick chat, or could you point me to the right person on the team? Thank you!
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