Senior Machine Learning Engineer (LLMs Knowledge Graphs)

We are looking for a Senior Machine Learning Engineer to join our team, with a specialized focus on Knowledge Graphs and LLMs. You will drive the development of AI products for our clients and participate in the development of a top-notch AI. At Factored we are building a company that we all hold as our own, every single one of us. We need your skills to help take this rocketship to new heights and help create new opportunities for us.  In return, you will be rewarded with an amazing team that supports you, rich culture, shared success and the flexibility to work– from the comfort of your home.

Functional 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 and query them using Cypher or SPARQL.
• Integrate knowledge graphs with LLMs using Retrieval-Augmented Generation (RAG) architectures to deliver actionable insights.
• Build robust APIs (FastAPI) and application services to implement relationship strength analysis and network traversal logic.

Qualifications:

• 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 fields
• 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 
• Ability to integrate relational databases and diverse external data sources into a unified graph.
• Excellent verbal and written communication skills in English.