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Google

SOC Performance Engineer, Google Cloud

Google

Published 16 May 2026
Tel Aviv, Israel
Full Time
27500 - 275000 people

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Role Highlights

Languages used

C++
SystemVerilog

Key skills

Machine Learning
Computer Science
Integrations
Electrical Engineering
CPU
Computer Architecture
SOC
Modelling
Debugging
TroubleShooting
Cloud
Infrastructure
Search
Security
Reliability
KPI

Tools, Libraries and Frameworks

Vertex AI
GCP
Verilog

Description

The role involves developing custom silicon solutions for consumer products. The engineer will utilize performance and power models to validate and tune designs against specific goals. Responsibilities include designing tests to verify system performance and developing technologies for benchmark representations in pre-silicon environments. The position requires analyzing complex problems to identify design weaknesses and resolving performance issues across pre- and post-silicon stages. Additionally, the engineer will create performance measurement frameworks and dashboards to support stakeholder decision-making.

Required Qualifications and Skills

Candidates must possess a Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience. A minimum of 8 years of experience in SoC or CPU performance and power modeling, analysis, and debugging is required. Applicants need expertise in computer architecture, specifically regarding interconnects, traffic QoS, distributed caches, and I/O flows. Proficiency in C or C++ programming is necessary, along with a demonstrated ability to identify and resolve performance problems.

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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