✦ Luna Orbit — AI & Machine Learning

Specialist, Maintenance Reliability Engineer II

at Bristol-Myers Squibb

📍 Bothell - WA - US Hybrid 💰 $102K – $123K USD / year Posted March 14, 2026
Salary $102K – $123K USD / year
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role involves designing and maintaining semantic data models and knowledge graphs to support enterprise AI and data integration efforts within a manufacturing environment.

  • Design and maintain ontologies
  • Build knowledge graphs
  • Collaborate with data engineers and stakeholders
  • Develop metadata schemas
  • Support AI/ML model pipelines

Focuses on ontology engineering, semantic web standards, data governance, and integration of knowledge graphs with enterprise data platforms to enable AI/ML applications.

The ideal candidate is an experienced ontology engineer with expertise in designing semantic data models, knowledge graphs, and data integration. They should be familiar with ontology standards like OWL, RDF, and SPARQL, and capable of collaborating across technical teams.

Ontology designKnowledge graphsSemantic data modelsData integrationCollaboration
AI/ML pipelinesData governanceMetadata managementEnterprise data platformsData visualization
OWLRDFSPARQLKnowledge graph platformsData governance tools
Ontology designKnowledge graphsSemantic data modelsOWLRDFSPARQLData governanceData integrationAI/ML pipelinesMetadata schemas
Ontology engineeringSemantic data modelsOWLRDFSPARQLKnowledge graphsData governanceData integrationAI/ML pipelinesTaxonomiesMetadata schemas
CollaborationCommunicationProblem-solvingAttention to detailTeamwork
Industry Manufacturing / Steel Industry
Job Function Designing semantic data models and knowledge graphs to enable AI and data integration
Role Subtype Maintenance Reliability Engineer II
Ontology EngineerSemantic data modelsOWLRDFSPARQLKnowledge graphsData governanceData integrationAI/ML pipelinesMetadata schemasOntology designData modelingData managementEnterprise data platformsData visualization

Lack of experience with ontology design or knowledge graphs, No familiarity with semantic web standards (OWL, RDF, SPARQL), Unwillingness to collaborate with cross-functional teams

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