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Google

Design Verification Engineer, Google Cloud Silicon

Google

Published 14 May 2026
Bangalore, India
Full Time
27500 - 275000 people

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Role Highlights

Languages used

SystemVerilog

Key skills

AI
Machine Learning
Integrations
Electrical Engineering
Control Systems
UVM
Cloud
Regression
Architecture
Reliability
Infrastructure
Data
Operations
Research

Tools, Libraries and Frameworks

Vertex AI
GCP
IOS
TPU
SOCs

Description

The role involves shaping the future of hardware acceleration by working on Tensor Processing Unit technology. The engineer will own the full verification life cycle, including planning, test execution, and coverage closure. Responsibilities include building constrained-random verification environments to ensure the reliability of hardware workloads. The position requires collaborating with design teams to identify verification scenarios and debug complex digital designs. The work focuses on meeting performance and accuracy goals for systems that power large-scale applications.

Required Qualifications and Skills

Candidates must possess a Bachelor's degree in Electrical Engineering or equivalent practical experience, with a Master's degree preferred. A minimum of 4 years of experience in digital logic verification at the RTL level is required. Applicants need expertise in verifying IP, subsystems, and SoCs, specifically within networking domains. Proficiency in creating constrained-random verification environments using SystemVerilog and UVM is necessary.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

Google

Size

275773

Website

goo.gle

HQ

Mountain View, US

Public/Private

Public Company

Description

At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.

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