Senior Silicon Design Verification Engineer
Google · Bengaluru · onsite · Posted 68d ago
Not disclosed8–10 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
Minimum qualifications:
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.
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 cutting-edge 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.
Responsibilities
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
- 8 years of experience creating and using verification components and environments in standard verification methodology.
- Experience verifying digital systems using standard IP components/interconnects (e.g., microprocessor cores, hierarchical memory subsystems).
- Experience with verification techniques and the full verification lifecycle.
- Experience with performance verification of ASICs and ASIC components.
- Experience with multiple SoC/IP projects/cycles in 3 or more products.
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- Experience with industry-standard simulators, revision control systems, and regression systems.
- Experience in Artificial Intelligence/Machine Learning (AI/ML) accelerators or vector processing units.
- Excellent problem-solving and communication skills.
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.
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 cutting-edge 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.
Responsibilities
- Plan the verification of digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification scenarios.
- Create and enhance constrained-random verification environments using SystemVerilog and Universal Verification Methodology. Verify designs with SystemVerilog Assertions and industry leading formal tools.
- Identify and write all types of coverage measures for stimulus and corner-cases.
- Debug tests with design engineers to deliver functionally correct design blocks.
- Close coverage measures to identify verification holes and to show progress towards tape-out.
Sourced from foundit
Skills
System VerilogIndustry standard simulatorsrevision control systemsregression systemsVerification TechniquesAI/ML AcceleratorsUniversal Verification Methodologyvector processing unitsArtificial IntelligenceMachine Learningverification componentsperformance verification of ASICs
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