Research Scientist / Research Engineer, Search - Knowledge Graphs

Job summary

Responsibilities

We’re looking for a Researcher to work on semi-structured knowledge graphs within Search. You’ll research and develop methods for mining structured information from heterogeneous, unstructured and semi-structured web content, making that information more accessible and useful to AI models.

• Develop methods to extract and connect structured information across diverse web sources, including entities, attributes, and relationships.
• Build scalable approaches for transforming noisy, inconsistent content into useful knowledge representations.
• Explore how models and compute can improve extraction quality and reduce the manual work involved in building knowledge systems.
• Design evaluations that measure both the quality of extracted knowledge and its usefulness for retrieval and model reasoning.
• Partner with researchers and engineers to integrate structured knowledge into Search and use model performance to guide improvements.

What they're looking for

• Deep experience in knowledge extraction, knowledge graphs, entity resolution, or related work that derives structure from large, heterogeneous datasets.
• Strong machine learning and research skills, with experience developing and evaluating methods for real-world data.
• A track record of building or scaling data and ML systems, particularly for web-scale extraction, indexing, or retrieval.
• Experience independently driving open-ended technical problems from an initial idea through experimentation and implementation.
• A first-principles approach to using AI and compute, with a willingness to rethink established methods as model capabilities improve.