Software Engineer, Search Modalities, Search Live Quality at Google

Belo Horizonte, MG

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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. In this role, you will develop a voice‑first conversational AI experience that enables multi‑turn audio interactions, delivering an intuitive, fluid conversational AI product with evidence‑based answers through advanced modeling, refined prompt engineering, and comprehensive Trust and Safety protocols in a secure user environment.

Requirements

Education

  • Bachelor's degree in Computer Science or other technical field

Experience

  • 1 year of experience with data structures or algorithms
  • 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript)

Skills

  • data structures
  • algorithms
  • Python
  • C
  • C++
  • Java
  • JavaScript
  • information retrieval
  • distributed computing
  • large-scale system design
  • networking
  • data storage
  • security
  • artificial intelligence
  • natural language processing
  • UI design
  • mobile
  • leadership
  • cross-functional collaboration
  • model evaluation
  • performance metrics
  • research
  • optimization (pruning, quantization)
  • performance improvements
  • new features

Languages

  • English

Responsibilities

  • Execute model evaluations and systematically document performance metrics (wins and losses).
  • Research and develop solutions to address and mitigate performance losses across the platform/organization.
  • Optimize machine learning models using various technical approaches (e.g., pruning, quantization) to enhance efficiency and latency.
  • Drive cross-functional collaboration to align efforts, maximize team impact, and reach across organizational boundaries.
  • Implement performance improvements and new features on core Mars flows using Kotlin.

Technologies

KotlinPython

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