Software Engineer II, Machine Learning, Search

vor 24 Stunden


Zürich, Schweiz Google Inc. Vollzeit
Software Engineer II, Machine Learning, Search

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Minimum Qualifications:
  • Bachelor’s degree or equivalent practical experience.
  • 1 year of experience with data structures or algorithms.
Preferred Qualifications:
  • Experience with building classifiers, machine learning, ranking, research background.
  • Experience in Machine Learning, Large Language Model, Data Analysis, and Search Quality.
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.

Responsibilities
  • Write 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).
  • Working with the latest technologies, including Gemini, to build classifiers: from simple and linear models to neural networks.
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