Senior Staff Software Engineer, Generative Retail Ad Formats and LLM Applications
Mountain View, CA, USA · Senior Staff · Full-time · Posted Sep 25, 2026
- Experience
- 8 years in software development and in testing, maintaining, or launching software products; 5 years in software design and architecture; 8 years with ML/AI algorithms and tools, deep learning, or other modeling; 7 years leading technical project strategy, ML design, and ML infrastructure; 2 years with GenAI.
- Education
- Bachelor's degree or equivalent practical experience.
About the job
Leads development of generative, interactive retail ad formats and LLM-powered systems for Google Shopping ads, from content generation and evaluation to serving and whole-page optimization.
What you'll do
- Set technical and product strategy, define roadmaps, and lead complex cross-team initiatives from design through launch.
- Own technical architecture and improve system bottlenecks, engineering quality, experimentation velocity, and production reliability.
- Partner across Ads Quality, Commerce, and Search to optimize retail ad products and whole-page layouts.
What they ask for
- Bachelor's degree or equivalent practical experience.
- 8 years of software development experience in one or more programming languages, including data structures and algorithms; 8 years testing, maintaining, or launching software products; and 5 years in software design and architecture.
- 8 years of experience with ML/AI algorithms and tools, deep learning, or other modeling; 7 years leading technical project strategy, ML design, and ML infrastructure; and 2 years with GenAI.
Nice to have
- PhD in Computer Science, Statistics, or a related field.
- Experience fine-tuning GenAI models, building large language models, or applying GenAI and ML to real-world content problems.
Pay
$262000 - $364000 (USD) base salary
Tools
LLMs, Gemini, GenAI, deep learning, ML infrastructure
AI focus
Develops and deploys generative AI and LLM applications for personalized retail ad formats, including content generation, evaluation, serving, and ML infrastructure.
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