Senior Design Verification Engineer

About the role

The Senior Design Verification Engineer role on the AI and Infrastructure team at Google Cloud focuses on shaping the future of AI/ML hardware acceleration by verifying custom TPU (Tensor Processing Unit) silicon. Day-to-day, you will own the full verification life-cycle for complex digital designs—planning verification, writing coverage measures, debugging with design engineers, and building constrained-random verification environments using SystemVerilog and UVM to ensure AI/ML workloads meet stringent performance and accuracy goals. The position is based in Bengaluru, Karnataka, India.

What you’ll do

• 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).

What you’ll bring

• 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 FPGAs or ASICs.
• Experience in verification and debug of IP/subsystem/SoCs in the Networking domain such as packet processing, bandwidth management, congestion control.
• Experience verifying digital systems using standard IP components/interconnects (e.g., microprocessor cores, hierarchical memory subsystems).

Nice to have

• 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.

Skills

Education

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.