Senior Quality Engineer, Gemini Enterprise Quality

Google Google · Big Tech · Sunnyvale, CA +1

Senior Quality Engineer for Gemini Enterprise Quality at Google Cloud AI Research. This role involves designing and implementing ML solutions, leveraging ML infrastructure, and focusing on quality assurance for AI products, particularly in specialized ML areas like speech/audio or reinforcement learning. The role requires experience in ML infrastructure, including model deployment and evaluation, and contributes to bringing AI innovations to real-world impact.

What you'd actually do

  1. Write and test product or system development code.
  2. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
  3. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  4. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  5. Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.

Skills

Required

  • software development
  • programming languages
  • testing software products
  • software design
  • software architecture
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • model deployment
  • model evaluation
  • optimization
  • data processing
  • debugging

Nice to have

  • Master's degree or PhD in Computer Science or related technical field
  • data structures and algorithms
  • technical leadership role
  • developing accessible technologies

What the JD emphasized

  • specialized ML areas
  • ML infrastructure
  • model deployment
  • model evaluation
  • optimization
  • data processing
  • debugging
  • Speech/audio
  • reinforcement learning

Other signals

  • Google Cloud AI Research team addresses AI challenges
  • aiming to push the state-of-the-art in AI
  • collaborate with product teams to bring innovations to real-world impact
  • Design and implement solutions in one or more specialized ML areas
  • leverage ML infrastructure
  • demonstrate expertise in a chosen field
  • 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging)