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Research Engineer, Social & Cognitive Computing, IHPC
A*STAR - Agency for Science, Technology and Research
Singapore, KSA
Full Time
Mid
3 weeks ago
PythonLLMsNeo4jGraphDBOntology designKnowledge graph modeling
Free
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PythonLLMsNeo4j
About the Role
We are seeking a Knowledge Engineer to design, construct, and maintain knowledge graphs from heterogeneous enterprise documents using LLMs. The role involves ontology design, knowledge extraction, and developing question-answering pipelines.
Key Skills for This Role
PythonLLMsNeo4jGraphDBOntology designKnowledge graph modeling
Responsibilities
- Leverage LLMs to extract structured knowledge from unstructured and semi structured documents
- Design, construct, and maintain knowledge graphs including schema and ontology design
- Implement and manage knowledge graph storage using graph databases such as Neo4j and GraphDB
- Develop LLM powered question answering and interaction pipelines over knowledge graphs
- Collaborate with domain experts and stakeholders to refine ontologies and use cases
Requirements
- Strong understanding of ontology design, knowledge graph modeling, and semantic data representation
- Proficiency in Python, with experience building data processing and NLP pipelines
- Solid understanding of prompt engineering and LLM based workflows
- Hands on experience with closed source and open source LLMs
- Experience with graph databases, particularly Neo4j and/or GraphDB
Full Job Posting
Job Summary
- The Knowledge Engineer will design, construct, and maintain knowledge graphs from heterogeneous enterprise documents
- Role involves leveraging LLMs for knowledge extraction, ontology driven structuring, and question answering over knowledge graphs
Key Responsibilities
- Leverage LLMs to extract structured knowledge from maintenance manuals, product design documents, troubleshooting guides, lessons learned reports
- Process documents in multiple formats including Word, PDF, PowerPoint, and Excel
- Design, construct, and maintain knowledge graphs: schema and ontology design, entity and relationship modelling, data normalisation and validation
- Implement and manage knowledge graph storage using graph databases such as Neo4j and GraphDB
- Develop LLM powered question answering and interaction pipelines over knowledge graphs
- Collaborate with domain experts and stakeholders to refine ontologies, extraction logic, and use cases
Required Skills & Experience
- Strong understanding of ontology design, knowledge graph modeling, and semantic data representation
- Proficiency in Python, with experience building data processing and NLP pipelines
- Solid understanding of prompt engineering and LLM based workflows
- Hands on experience working with LLMs, including closed source and open source models
- Experience with graph databases, particularly Neo4j and/or GraphDB
Preferred / Advantageous Skills
- Experience in information extraction, document understanding, or NLP pipelines
- Familiarity with RDF, OWL, SPARQL, or Cypher
- Experience integrating LLMs with structured knowledge sources
Key Competencies & Attributes
- Strong analytical and problem solving skills
- Ability to work independently while collaborating within a multidisciplinary team
- Good communication skills to engage with technical and non technical stakeholders
- Demonstrated willingness to continuously learn and keep up with advances in LLMs, NLP, and knowledge engineering
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