51 to 72 of 72 Ontologies Jobs in London

classification levels (e.g., OFFICIAL-SENSITIVE to SECRET), and military decision-making cycles. Palantir Platform Strategy: Understanding how to leverage Palantir (Gotham/Foundry?) capabilities, ontology design, and data integration pipelines to deliver value without rebuilding native features. Roadmap & Prioritisation: Ability to prioritise high-value data feeds and features under strict … Strategy: Data Fusion Strategy, Dual-Persona UX (Tactical vs. Strategic), Product Roadmap, Capability Management, Operational Value Delivery. Technical Familiarity: Palantir Foundry, Palantir Gotham, Data Ontologies, Edge Architecture, APIs, Situational Awareness Tools. Important Information Start Date: ASAP Security Requirements: Minimum clearance required is SC - due to the nature of the role ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with end-to-end data pipeline ...

engineering, generative AI, LLM, and multi-modal models look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Well versed in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience with ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Well versed in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience with ...

define what staying at the forefront means for the practice drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value … degree or equivalent, plus all of the following: Significant experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Advanced practical knowledge of schema design, ontology management, and KG curation Seasoned in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience ...

define what staying at the forefront means for the practice; drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value … degree or equivalent, plus all of the following: Significant experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Advanced practical knowledge of schema design, ontology management, and KG curation Seasoned in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience ...

ability to read schemas, review queries, and discuss data modeling trade-offs with engineers Understanding of graph data modeling concepts including nodes, edges, properties, ontologies and taxonomies, RDF vs property graphs, and entity resolution Proven track record of translating ambiguous business problems into precise functional and non-functional engineering requirements … transparent backlog with clear value hypotheses, success metrics, and prioritization rationale Translate ambiguous business problems into precise functional and non-functional requirements covering ontology scope, data sources, query patterns, latency and scale targets, access controls, and integration points Own the product roadmap for the Knowledge Graph platform, run agile ceremonies ...

full provenance. Where you land depends on you and on what the lab needs next. Any of these could be yours: Data infrastructure and ontology underpinning our data ingestion, workflows and output APIs that receive customer intent, translate it into workflows and return results - followed quickly by MCP servers … automation, robotics, manufacturing, logistics, scientific instruments, or energy). Orchestration, scheduling, or workflow-engine work, and distributed systems at scale. Data-intensive systems: pipelines, ontologies or knowledge graphs, provenance or lineage. Early-stage or founding-engineer experience at a venture-backed company. Why this is unusual Most software roles like ...

with AI, automation, and product innovation across the portfolio. How you will make an impact: Define and own the canonical telco data model and ontology across network topology, service lifecycle, inventory, assurance, and OSS domainsAlign data models with industry standards including TM Forum Open APIs, SID/eTOM, Open Digital … Architecture, YANG/NETCONF, and TOSCADrive adoption of ontology models across product teams as the semantic foundation for data exchange, AI training, and digital twin deploymentDevelop and lead the data fabric product architecture, including federated access, streaming pipelines, virtualization, metadata management, and lineage trackingTranslate data architecture vision into scalable, cloud ...

complex modalities such as genomics, transcriptomics, imaging, clinical and real-world datasets. Partner with the Data Excellence community and IT to align on governance, ontologies, metadata harmonisation, stewardship and shared enterprise data foundations. Establish ways of working and coach other team members, onboarding, mentoring and technically leading data engineers … requirements, including versioning, reproducibility and tensor-based workflows for large-scale AI systems. Experience implementing data governance in practice, including metadata management, lineage, provenance, ontologies, cataloguing and FAIR principles and familiarity with Trusted Research Environments (TREs) and controlled-access research data environments. Strong collaboration and influencing skills across technical ...

team in London, London, City of (GB-LND), United Kingdom (GB).Job Title: Knowledge Graph ArchitectExperience: 10+ years (5+ years in Knowledge Graphs/Ontology Engineering)Role OverviewWe are looking for a Knowledge Graph Architect to lead the design and governance of enterprise knowledge graphs. This role will define … ontology, data model, and canonical vs. interpretive boundaries, enabling scalable, high-quality graph data for AI-driven use cases, including Graph RAG.The role also requires strong team leadership, including coaching, mentoring, and building internal capabilities. Key ResponsibilitiesArchitecture & DesignDefine node types, relationships, schemas, and property standardsDesign scalable and extensible graph data ...

into the team’s roadmap. Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems. Domain & Research Integration Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems. Incorporate structured data — including datasets, chemical entities, genes, drugs … Computer Science, Data Science, Machine Learning, or a related field Experience working with large-scale datasets (scientific, biomedical, or enterprise data) Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef) Exposure to production ML systems and MLOps practices Familiarity with data visualization and analytical tooling (e.g., Tableau ...

Accuracy: Serve as the crucial "human in the loop," auditing, fine‐tuning, and optimizing LLM‐generated classifications, descriptions, and data extractions. Architect the ETF Ontology: Build, refine, and maintain a single source of truth—our unified ETF taxonomy and ontology—to set the standard for asset class categorization. Ensure Uncompromising … Science, Data Analytics, or a related quantitative field. Bonus Points: Existing relationships with major financial market data vendors and direct experience building taxonomy/ontology frameworks. Salary Range: $80,000K/year - $90,000K/year USD Please note that the Salary Range included is a guideline only. The salary ...

integration infrastructure Reconcile and unify data from multiple, heterogeneous sources Develop flexible ways to model and interpret unfamiliar data Shape the semantic models and ontologies that give business data consistent meaning Design reliable, observable orchestration for complex data workflows Establish strong foundations for data quality, lineage and observability Embed permissions … ClickHouse or DuckDB Experience with distributed systems and third-party integrations A pragmatic mindset and a strong bias towards shipping Experience with semantic models, ontologies or knowledge graphs would be a bonus. You don’t need to meet all the requirements. We care more about what you’ve built ...

remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. … degree or equivalent, plus at least 4 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) solid experience in schema design, ontology management, and KG curation Proven experience in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with ...

remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. … degree or equivalent, plus at least 4 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) solid experience in schema design, ontology management, and KG curation Proven experience in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with ...

user stories, and acceptance criteria. Data & Workflow Mapping: Documenting current-state data flows across command nodes and defining target-state fused data workflows. Palantir Ontology Alignment: Working with Data Specialists to map real-world military assets, events, and relationships into the Palantir object model. Traceability & Compliance: Maintaining traceability between operational … Stories, Acceptance Criteria (Gherkin), Gap Analysis, Process Mapping, Target Operating Model (TOM). Data & Domain: Data Dictionary Creation, Operational Workflows, C2 (Command & Control) Workflows, Ontology Alignment, Data Traceability. Stakeholder & Governance: Military Stakeholder Engagement, Subject Matter Expert (SME) Facilitation, MoD Procurement Awareness, DefStan Compliance. Important Information Start Date: ASAP Security Requirements ...

customer's business - P&L drivers, operating model, competitive pressures, and regulatory environment. Speaks insurance fluently, or has fluency in financial services technology. Insurance Ontology and AutonomousInsurer thesis: Carries the Sapiens point of view into every engagement - articulating why a shared data model across the insurance value chain creates structural … task. Leads the full talent lifecycle with candour and integrity. Sapiens ambassadorship: Carries the Sapiens point of view into customer environments. Knows the Insurance Ontology argument, the AutonomousInsurer thesis, and the AI moat – and can hold them in a room. Leads the Programme's PM team, setting standards and driving ...

Описание Spectrum is a JetBrains startup incubator project that collects data from code, documentation, and issues, organizing it into a unified ontology for AI agents to search and reason over. It aims to provide a living specification and a single source of truth for product and architectural knowledge in software … ability to explain complex technical concepts to diverse audiences; Proficiency in English, both written and verbal; Nice to have: Kotlin knowledge, experience with ontologies, knowledge graphs or graph-based reasoning, early-stage startup experience, strategic thinking about product-led AI, background in code analysis, developer tools or software engineering research ...

define entities attributes relationships cardinality Experience modelling complex domains with many-to-many relationships hierarchical structures rule-based logic Experience in knowledge graph modelling ontology tools (e.g. Protégé) graph concepts (nodes, edges, traversal) Experience in regulated environments (government, finance) Conduct knowledge discovery across the organisation, working with stakeholders to understand … domains Translate unstructured understanding into structured artefacts (models, diagrams, definitions) Develop conceptual and logical data models to underpin knowledge graphs Support the creation of ontology and taxonomy models Enable downstream teams to build knowledge graphs RAG pipelines AI retrieval systems Public sector background Location: Remote with key meetings in Manchester ...

contribute recommendations for experimentation and adoption. Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts. Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows. Search, Retrieval & RAG Systems Design, develop, and optimize search and retrieval pipelines , including lexical, vector, and hybrid retrieval approaches. … conversational AI applications Experience working on search, ranking, recommendation, or retrieval systems Familiarity with scientific, biomedical, or scholarly datasets Experience with knowledge graphs, ontologies, or semantic enrichment systems Exposure to production ML systems and MLOps practices Academic or industry research experience in NLP, information retrieval, search, or generative AI Experience ...

ecosystems. Establish AI quality engineering practices, including agent evaluation frameworks, synthetic data strategies and agentic testing methodologies. Design and scale enterprise knowledge architectures, ontologies and retrieval systems that enable trustworthy, context-aware AI experiences. Work model We believe hybrid work is the way forward as we strive to provide flexibility … such as Copilot Studio or Agentforce, and MCP/A2A agent protocols. Expertise in RAG-at-scale and grounding strategy, plus knowledge graph and ontology engineering. Agentic test-framework design experience together with AI security and access controls. These will help you succeed AI-native solution architecture expertise paired with ...