Software Engineer, Engineering Productivity, Pixel Tools
Indexed description
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 1 year of experience coding in one of the following programming languages: Python, Java, or SQL.
- Master's degree in Computer Science or a related technical field.
- Experience in automating routine engineering tasks, particularly in the areas of issue triaging, root-cause analysis, or system health monitoring.
- Experience with software telemetry and analyzing large datasets to derive actionable insights for product quality.
- Ability to collaborate with cross-functional teams to understand domain-specific triage needs and translate them into scalable AI/ML solutions.
- Excellent problem-solving skills with a focus on improving engineering productivity and reducing operational costs.
As a member of the Pixel System Health Engineering Productivity team, you will build "radically helpful superpowers" for Pixel users by applying cutting-edge AI to hardware engineering. You will develop intelligent automation systems like BugLens using Google’s Gemini models to transform how we triage bugs and justify device quality. Your work will reduce manual engineering effort, save costs, and significantly speed up the delivery of high-quality products. By collaborating with teams across the Pixel organization, you will play a key role in ensuring every Pixel device is stable, high-performing, and reliable.
Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
Responsibilities
- Develop and scale automated triage systems using GenAI and Machine Learning (such as Gemini) to identify, deduplicate, and route issues across the Pixel ecosystem.
- Build predictive tools that leverage AI/ML to justify device quality, helping engineers identify system health anomalies and justify product readiness.
- Partner with cross-functional Pixel teams (Stability, Display, Sensor, etc.) to integrate and drive adoption of AI-powered engineering tools.
- Visualize system metrics to provide deep product insights, enabling data-driven decisions to improve device performance and reliability.
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