Machine Learning Engineer (LLMs Knowledge Graphs)
F
FactoredArtificial Intelligence
Latin AmericaFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- PythonFastAPILLM
Requirements
- 5+ years of hands-on experience developing and deploying machine learning models in production environments.
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
- Hands-on experience with knowledge graph technologies, specifically property graph (Neo4j) or RDF frameworks.
- Proficiency in querying systems using Cypher and/or SPARQL.
- Hands-on experience with AWS Neptune, GraphDB, or Memgraph for building production-grade Knowledge Graphs.
- Strong skills in ontology design and modeling complex entity relationships.
- Expert-level Python development skills for building enterprise-grade applications.
- Experience building Retrieval-Augmented Generation (GraphRAG) and AI-driven recommendation systems.
- Strong knowledge of embeddings, vector databases, and semantic search techniques.
- Hands-on experience with major cloud platforms such as AWS, Azure, or GCP.
- Experience working with FastAPI/Flask.
- Excellent verbal and written communication skills in English.
Responsibilities
- Design and implement knowledge graph architectures using property graph (Neo4j) or RDF-based models.
- Transform structured and semi-structured data into optimized graph structures.
- Query graph data using Cypher or SPARQL.
- Integrate knowledge graphs with LLMs using Retrieval-Augmented Generation (RAG) architectures.
- Build robust APIs (FastAPI) for application services.
- Implement relationship strength analysis and network traversal logic.
View Full Description & ApplyYou'll be redirected to the employer's site
