Knowledge Graph Algorithm Intern

Skills

About the Role

You will help design domain knowledge graph ontologies and schemas, including entities, relationships, attributes, and events. You will build LLM-agent knowledge extraction pipelines, create agent workflows, perform knowledge fusion and disambiguation, write results to graph databases, and experiment with GraphRAG and KGQA systems.

Requirements

• Be a current undergraduate or higher student in computer science, artificial intelligence, NLP, data science, or a related field
• Use Python and demonstrate independent debugging ability
• Understand knowledge graph concepts including entities, relationships, triples, ontologies, RDF, OWL, SPARQL, and Cypher
• Understand agent paradigms including planning, tool use, memory, reflection, and multi-agent systems
• Have used at least one agent or LLM framework
• Understand prompt engineering and large language model APIs
• Understand NLP tasks including named entity recognition, relation extraction, event extraction, text classification, and vector retrieval

Responsibilities

• Design domain knowledge graph ontologies and schemas
• Build LLM-agent knowledge extraction pipelines
• Design agent workflows for planning, tool use, memory, reflection, and result validation
• Perform entity alignment, conflict detection, and quality evaluation
• Write knowledge graph results to graph databases
• Apply GraphRAG and KGQA for retrieval, reasoning, and multi-hop question answering
• Track relevant advances, reproduce experiments, and share technical findings internally