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Google

Software Engineer, Engineering Productivity, Pixel Tools

Google

Published 16 May 2026
Taiwan
Full Time
27500 - 275000 people

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Role Highlights

Languages used

Python
Java
SQL

Key skills

AI
NLP
Information Retrieval
Machine Learning
Computer Science
System Design
Full Stack
DataSets
Search
Storage
Security
UI
Automation
Reliability

Tools, Libraries and Frameworks

Android
ADS

Description

The role involves developing and scaling automated triage systems to identify and route issues across the Pixel ecosystem. The engineer will build predictive tools that leverage artificial intelligence to justify device quality and identify system health anomalies. Collaboration with cross-functional teams is required to integrate and drive the adoption of these engineering tools. Additionally, the position entails visualizing system metrics to provide product insights that support data-driven decisions. The work focuses on reducing manual engineering effort and improving device performance and reliability.

Required Qualifications and Skills

The role requires a Bachelor's degree or equivalent practical experience. Candidates must possess at least one year of coding experience in Python, Java, or SQL. A Master's degree in Computer Science or a related technical field is preferred. Additionally, experience in automating routine engineering tasks, software telemetry, and analyzing large datasets is considered beneficial.

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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