Senior System Validation Test Engineer, Pixel Watch

Google Google · Big Tech · Mountain View, CA +1

This role focuses on system validation test engineering for the Google Pixel Watch. The engineer will design and develop test features, automate testing, create tools, and manage the end-to-end data ecosystem for system validation metrics. Responsibilities include developing test infrastructure, integrating AI into the validation ecosystem, translating user journeys into automation frameworks, automating data analysis, and integrating new test features. The role emphasizes full-stack validation engineering and aims to improve test efficiency and engineering productivity.

What you'd actually do

  1. Develop and optimize watch system validation test infrastructure and databases to ensure scalable, high-performance testing capabilities.
  2. Drive the integration of AI and emerging technologies into the validation ecosystem for consumer products, significantly advancing test efficiency and engineering productivity.
  3. Translate complex Critical User Journeys (CUJs) from Product Requirement Documents (PRDs) into specialized automation frameworks and physical test setups to drive validation excellence.
  4. Automate data analysis and visualization pipelines to streamline issue debugging and accelerate root-cause analysis.
  5. Integrate new test features into lab and factory stations, expanding test coverage to adapt to evolving product requirements.

Skills

Required

  • coding
  • developing test methodologies
  • writing test plans
  • creating test cases
  • debugging
  • test automation frameworks
  • test automation
  • test infrastructure
  • test script development
  • test equipment

Nice to have

  • Master's degree or PhD in Computer Science, Electrical Engineering, or a related field
  • scaling automated test frameworks across lab and factory environments
  • architecting robust automation tools
  • optimize system validation workflows using Python and Linux shell scripting
  • streamlining debugging and root-cause analysis through custom dashboarding/automated data visualization pipelines for large datasets
  • advance validation databases and test infrastructure by driving the integration of AI and next-gen engineering tools
  • Ability to translate high-level Critical User Journeys and PRD requirements into specialized automation frameworks/physical test configurations

What the JD emphasized

  • AI and emerging technologies into the validation ecosystem
  • Automate data analysis and visualization pipelines
  • critical infrastructure upgrades
  • intelligent log file parsers
  • rapid debugging utilities
  • AI and next-gen engineering tools