Staff Software Engineer, Ai-powered Retail Ad, Content and Creative Automation

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

Staff Software Engineer at Google focused on AI-powered retail advertising, content, and creative automation. The role involves designing and launching new ad formats, developing and tuning LLM-based content generation systems, running experiments, and leading the strategy for next-generation Shopping Ads. Requires significant experience in software engineering, ML infrastructure, and ML design.

What you'd actually do

  1. Design, implement and launch new shopping ad formats and system optimizations to help users in their shopping journey.
  2. Design, develop and tune LLM-based content generation, prompt optimization and evaluation for products.
  3. Run and analyze experiments to ensure that the new shopping ad formats help users, advertisers and Google.
  4. Lead the strategy and roadmap for the next gen of Shopping Ads Formats. Guide junior engineers and provide technical leadership.
  5. Collaborate with cross-team partners within Ads as well Cross-Product Area on designs and launches. Build a strong collaboration with cross-functional (PM/UX/TPM) stakeholders and other TLs/UTLs and positively influence products and projects.

Skills

Required

  • Python
  • C++
  • Software design
  • Software architecture
  • ML infrastructure
  • Model deployment
  • Model evaluation
  • Data processing
  • Debugging
  • Fine tuning
  • Speech/audio processing
  • Reinforcement learning

Nice to have

  • Master's degree
  • PhD
  • Data structures
  • Algorithms
  • Cross-functional project experience
  • Technical leadership

What the JD emphasized

  • 8 years of experience programming in Python or C++
  • 5 years of experience testing, and launching software products
  • 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 3 years of experience with software design and architecture.

Other signals

  • LLM-based content generation
  • prompt optimization
  • evaluation for products
  • ML infrastructure
  • model deployment
  • model evaluation
  • data processing
  • debugging
  • fine tuning