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Google

RTL Design Engineer, Cloud Silicon

Google

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

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Role Highlights

Languages used

SystemVerilog
Python
Perl

Key skills

Machine Learning
Computer Science
Integrations
Electrical Engineering
SOC
Cloud
Testing
Data
Architecture
Infrastructure
Search
Security
Reliability

Tools, Libraries and Frameworks

Vertex AI
GCP
Verilog
IPS
FirmWare

Description

The role involves developing custom silicon solutions to power consumer products and data center infrastructure. The individual will contribute to the design of application-specific integrated circuits used to accelerate machine learning computation. Responsibilities include owning the microarchitecture and implementation of intellectual property and subsystems. The engineer will collaborate with cross-functional teams to specify and deliver designs while evaluating options for complexity, performance, and power. Additionally, the position requires driving design methodology, code reviews, and identifying improvements for power and area efficiency.

Required Qualifications and Skills

Candidates must possess a Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field. A minimum of four years of experience in ASIC development is required, specifically utilizing Verilog, SystemVerilog, VHSIC, Hardware Description Language, or Chisel. Applicants must demonstrate experience with micro-architecture, IP design, and ASIC design verification processes. Proficiency in English is a requirement for this role.

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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