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Software Engineer, AI/ML, Search Personalization

Google
Posted 15 hours ago, valid for 23 days
Location

Mountain View, CA, US

Salary

$147,000 - $210,000 per year

Contract type

Full Time

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Sonic Summary

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  • Google is seeking a software engineer with a Bachelor's degree and at least 2 years of software development experience, including 1 year in C++ and 1 year building recommendation systems.
  • Candidates should have experience integrating generative AI tools into workflows and a strong understanding of data structures and algorithms.
  • The role involves writing development code, collaborating on design and code reviews, and contributing to documentation and educational content.
  • Engineers will work on critical projects that impact billions of users, focusing on complex engineering challenges and expanding Google's infrastructure.
  • The salary range for this position is between $147,000 and $210,000, along with a 15% bonus target, equity, and benefits.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  • 2 years of experience with software development in C++ programming language.
  • 1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.
  • 1 year of experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • 2 years of experience with data structures and algorithms.
  • Experience developing accessible technologies.
  • Experience developing algorithms (e.g., ranking, recommendations, prediction, search quality, personalization) and software that generates suggestions based on various input and output goals.

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.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

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

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

  • Write product or system development code. 
  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • 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/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.



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