Mid
Build the AI-powered test infrastructure that ships Pixel devices faster
Google's Platforms and Devices org is hiring a software engineer to build and own cross-device test infrastructure for Pixel, applying ML/AI to automate testing and speed up release cycles. Expect coding, ML infrastructure, and system-design depth across desktop, mobile, and device environments.
Step into this interview
Free · a live voice mock calibrated to this exact role
Likely format
Google SWE loop: phone screen with coding, then onsite/virtual onsite rounds mixing coding (DS&A), a Googleyness/leadership behavioral, and a domain round on ML infra or test systems.
What this interview tests
- Test infrastructure design at scale
- ML infrastructure (deployment, evaluation, optimization, data processing)
- Cross-device/platform debugging (hardware, network, service)
- Data structures & algorithms
- Code review and engineering best practices
Common question themes
Design a scalable test system for a new cross-device feature
Where would you apply ML/AI to reduce manual test triage
Debug a flaky test failure across hardware and service layers
Data structures/algorithms coding problem
Experience with ML infra: model deployment or evaluation pipeline
How you balance speed vs. test coverage in fast release cycles
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