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Open nowFirst seen 2 hours ago

Staff Software Engineer, Front-end, AI Surfaces

Google3,345 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowStaff Software Engineer, Front-end, AI SurfacesGoogle · Mountain View, CA, USA
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The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.5%3 days
  3. 8.1%7 days
  4. 15.1%14 days
  5. 33.9%30 days
This job: first seen 2 hours ago

Google median: 26 days open

The posting

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in full-stack software development with focus on front-end and user interface.
  • Experience using GenAI for development and experience issues.
  • Experience with Generative AI data, evaluation methodologies, and data quality.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures/algorithms.
  • Experience in building user experiences.
  • Expertise in front-end engineering and app development.
  • Apply product knowledge to conduct hypothesis testing.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Google AI Mode fundamentally rethinks the search experience, moving from blue links to a native conversational experience. Rethinking the ads experience requires end-to-end search ads thinking where ads feel native to this surface. Google AI mode also gets a different set of queries that are very research-oriented, where the type of ads and advertisers are very different from a regular search results page. You will experiment with new formats to seamlessly integrate ads and monetize AI-native surfaces.

Google AI Mode has rewritten its stack from the ground up with DevAI and GenAI, providing opportunities to improve and innovate our infrastructure. You will build AI-native experiences, working with stakeholders across the organization to advocate for new AI monetization concepts from ideation to launch.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Innovate from the ground up to build native ads experiences in AI-mode.
  • Leverage AI and Machine Learning (ML) advancements, including Large Language Models (LLMs), Agentic AI, and Dev-AI, to build solutions.
  • Collaborate across User Experience (UX), Product Management, Data Science, and other key ads quality stakeholders.
  • Evaluate and maintain high-quality standards across all ad experiences.
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