Google's software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information. Centerpiece provides the foundational ground truth on what content is truly essential on any webpage, enabling Google's search ranking algorithms, generative AI features, and LLM pretraining pipelines to focus strictly on high-signal content. In Google Search, the team is reimagining what it means to search for information, solving complex engineering challenges and expanding infrastructure to maintain a universally accessible and useful experience for people around the world.
Tasks
- Launch new versions of Centerpiece by improving the (prompted) Professor model, applying the Computer Use Agent, and training better student models.
- 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).
- Improve the tooling and infrastructure.
- Maintain or ablate other systems that provide similar data, re-directing the clients to Centerpiece.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.
Requirements
- 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.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- Experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
- Master's degree or PhD in Computer Science or related technical fields (preferred).
- 2 years of experience with data structures and algorithms (preferred).
- Experience developing accessible technologies (preferred).
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Über uns
Das Team
The Search team at Google is focused on reimagining information search and solving complex engineering challenges to provide a universally accessible and useful experience.