Senior Design Verification Engineer, Silicon, Google Cloud
Google · Bengaluru · onsite · Posted 68d ago
Not disclosed8–10 yrsfulltimeSourced from
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About this role
Minimum qualifications:
In this role, you will own the full verification life-cycle from verification planning and test execution to coverage closure, with an emphasis on meeting stringent AI/ML performance and accuracy goals, build constrained-random verification environments capable of exposing corner-case bugs and ensuring the reliability of Artificial Intelligence/Machine Learning (AI/ML) workloads on hardware. You will collaborate closely with design and verification engineers in active projects and perform verification.
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 force 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 in verification, verifying digital logic at RTL level using SystemVerilog or Specman/E for Field Programmable Gate Arrays (FPGAs) or ASICs.
- Experience in verification and debug of IP/subsystem/SoCs in the networking domain such as packet processing, bandwidth management, and congestion control.
- Experience verifying digital systems using standard IP components/interconnects (e.g., microprocessor cores, hierarchical memory subsystems).
- 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.
- Experience with the full verification life cycle.
- Excellent problem-solving and communication skills.
In this role, you will own the full verification life-cycle from verification planning and test execution to coverage closure, with an emphasis on meeting stringent AI/ML performance and accuracy goals, build constrained-random verification environments capable of exposing corner-case bugs and ensuring the reliability of Artificial Intelligence/Machine Learning (AI/ML) workloads on hardware. You will collaborate closely with design and verification engineers in active projects and perform verification.
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 force 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 and interact with design engineers to identify important verification scenarios.
- Identify and write all types of coverage measures for stimulus and corner-cases.
- Debug tests with design engineers to deliver functionally correct design blocks.
- Measure to identify verification holes and to show progress towards tape-out.
- Create a constrained-random verification environment using SystemVerilog and Universal Verification Methodology (UVM).
Sourced from foundit
Skills
verificationSystem VerilogDebugIndustry standard simulatorscongestion controlpacket processingrevision control systemsregression systemsSpecman einterconnectsbandwidth managementAI/ML Acceleratorsvector processing unitsArtificial IntelligenceMachine LearningIP subsystem SoCshierarchical memory subsystemsMicroprocessor Coresconstrained-random verification environmentsfull verification life cyclestandard IP components
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