Senior Software Engineer, Discover Ads User Value

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

Senior Software Engineer role focused on the user value of Discover Ads, involving engineering, data analysis, and product thinking to optimize ad auctions, inventory, and pricing. The role aims to improve advertiser, user, and Google values by leveraging product intuition, data insights, and research discoveries. It requires experience in software development, testing, and architecture, with a preference for experience in building and deploying recommendation systems.

What you'd actually do

  1. Write and test product or system development code.
  2. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  3. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  4. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  5. 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.

Skills

Required

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Nice to have

  • Master's degree or PhD in Computer Science, or a related technical field.
  • 5 years of experience with data structures and algorithms.
  • 1 year of experience building and deploying information retrieval or recommendation systems (e.g., retrieval, prediction, ranking, personalization) in production.
  • 1 year of experience in a technical leadership role.
  • Experience in data analysis or quality.

What the JD emphasized

  • 1 year of experience building and deploying information retrieval or recommendation systems (e.g., retrieval, prediction, ranking, personalization) in production.

Other signals

  • AI/ML is used to improve advertiser, user, and Google values
  • The role involves hypothesis validation through design, implementation, and A/B testing
  • Experience in building and deploying information retrieval or recommendation systems in production is preferred