Software Engineer II, Co-op and Marketplaces
Retail Advertiser Experiences (RAX) is responsible for one of the most critical areas in online advertising - retail. Retail Ads bring Google multiple billions in business, and our mission is to understand the retailers' needs and build advertising products that would deliver more value to them and to Google.
The Cooperative Advertising (Coop) team is developing the core infrastructure that powers Retail Media Networks (RMN) within Google Ads. Our platform empowers retailers to partner with brands to run Google Ads campaigns that drive high-value traffic directly to their storefronts, while seamlessly sharing conversion data.
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug, track, and resolve them by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Write product or system development code; Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Evolve Google Ads architecture to support complex brand-retailer relationships and scale the systems to manage massive global traffic. Build solutions end-to-end, addressing critical backend issues—such as engineering a resilient, low-latency streaming pipeline and unifying our measurement infrastructure.
- Drive user-facing innovations in the Google Ads Frontend.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 1 year of experience with data structures and algorithms.
- 1 year of experience with full-stack development.
Preferred qualifications:
- Master's degree in Computer Science, or a related technical field.
- Experience in online advertising or search quality.
- Expertise in experiment definition and analysis.
- Experience with large-scale ML systems or LLMs.
- Proficiency with large-scale streaming and batch processing systems.