4 of 4 Ontologies Jobs in the South East

streaming responses, async inference jobs, and robust error/retry semantics. Palantir Foundry Integration Work with Palantir Foundry to build and maintain data pipelines, ontologies, and integrations that connect backend services to Foundry-based analytics and workflows. Leverage Foundry's APIs and tooling to support data modelling, transformation, and secure ...

/CD & Agile delivery experience Good understanding of structured and unstructured data, and the techniques needed to exploit them in different ways, including schemas, ontologies, taxonomies and translation/representation issues. Background in Defence/Public Sector/secure environments highly desirable A curious, hands-on mindset with strong stakeholder ...

with stakeholders across engineering, operations, and leadership. What You Will Be Doing: Design and deliver enterprise-scale solutions on Palantir Foundry Build data pipelines, ontologies, and operational applications Develop data products and decision intelligence tools used day-to-day Translate complex operational problems into scalable technical solutions Contribute to platform … modern data architectures & distributed systems Ability to work in fast-paced, ambiguous environments Excellent stakeholder engagement and communication skills Experience building: Data pipelines & transforms Ontologies and data models Operational workflows/application Desirable Experience: Experience with Palantir AIP or AI-enabled workflows Exposure to LLMs or agentic AI systems Cloud ...

strategy across data harmonisation, pipeline validation, knowledge graph, and FAIR data product requirements. Requirements Translation: Translate ambiguous scientific requirements into clear canonical data models. Ontology Management: Make ontology reuse, extension, and mapping decisions (with documented rationale), and define persistent identifiers and consistent provenance fields. Risk Mitigation: Identify modelling risks early … including metadata gaps, ontology conflicts, source data quality issues, lineage gaps, and downstream compatibility risks. Design & Architecture: Design modular, reusable, and future-proof models aligned to FAIR principles (findability, accessibility, interoperability, reusability) and enterprise standards. Technical Implementation: Apply practical experience with LinkML (or equivalent), including classes, slots, ranges, identifiers, constraints ...