Join a forward-thinking team dedicated to crafting bespoke silicon solutions that will power Google's future direct-to-consumer products. You will be instrumental in driving innovation for products cherished by millions globally.

Your expertise will be pivotal in defining the next wave of hardware experiences, consistently delivering exceptional performance, efficiency, and seamless integration.

Develop comprehensive test plans, detailing verification strategies, environments, components, stimuli, checks, and coverage metrics, ensuring clear and accessible documentation.

Strategize and execute the verification of digital design blocks by thoroughly understanding design specifications and collaborating closely with design engineers to pinpoint crucial verification scenarios.

Construct and enhance constrained-random verification environments utilizing SystemVerilog and UVM, with the option to integrate SystemVerilog Assertions (SVA) and formal tools for advanced formal verification.

Conduct power-aware simulations and formal verification to validate power management functionalities such as clock gating, power gating, and DVFS. Create and implement power-aware test cases, including stress and corner-case scenarios, for robust power integrity.

Execute coverage-driven verification plans to guarantee thorough validation of ASIC designs. Partner with design engineers to address coverage gaps and elevate overall design quality.

Possess a Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a closely related discipline, or demonstrate equivalent practical experience.

Gain at least 1 year of hands-on experience in developing and utilizing verification components and environments within the UVM methodology at the IP or Subsystem level.

Demonstrate a proven track record in developing and maintaining design verification (DV) testbenches, test cases, and comprehensive test environments.

Preferred candidates will hold a Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with a specialization in computer architecture. Experience with image processing, computer vision, or machine learning IPs, along with familiarity with AMBA (APB/AXI/ACE) or other standard protocols, is highly valued. A foundational understanding of CPU, GPU, or other computer architectures is also beneficial.