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Software Engineer, Generative AI, Search Ads Personalization

Job

Google

Mountain View, CA (In Person)

Full-Time

Posted 1 day ago (Updated 10 hours ago) • Actively hiring

Expires 6/28/2026

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Job Description

Software Engineer, Generative AI, Search Ads Personalization corporate_fare Google place Mountain View, CA, USA bar_chart Mid Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
Minimum qualifications:
Bachelor's degree or equivalent practical experience. 2 years of experience programming in Python or C++. 1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). Experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models) and experience with text, image, video, or audio generation.
Preferred qualifications:
Master's degree or PhD in Computer Science, or a related technical field. 2 years of experience with data structures and algorithms. Experience developing and optimizing machine learning algorithms for personalization, ranking, and content recommendation. About the job In this role, you will collaborate across GenAI teams to create and execute on a goal and roadmap to ensure that users feel connected with our GenAI Ads. Responsibilities Write and test product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Build model and architectural components that provide effective attention for ads over user preferences and history. Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.