20 of 20 Ontologies Jobs in London

Doing Designing and developing scalable solutions within Palantir Foundry Building data pipelines, data models and data integration solutions Developing and maintaining Foundry Ontologies Creating high-quality, governed data assets for operational, analytical and AI use cases Building user-facing applications using low-code and pro-code capabilities Working directly with ...

Doing Designing and developing scalable solutions within Palantir Foundry Building data pipelines, data models and data integration solutions Developing and maintaining Foundry Ontologies Creating high-quality, governed data assets for operational, analytical and AI use cases Building user-facing applications using low-code and pro-code capabilities Working directly with ...

Deployment or promotion through environments. Operational support and troubleshooting. Experience dealing with: Performance issues or optimisation tasks. Permissions and basic security models. Schema/ontology changes and their impact on downstream use cases. Integration problems and incident recovery in collaboration with senior staff. Some client-facing experience (e.g. workshops, demos ...

will help define and drive the capabilities, patterns and practices needed to make enterprise data AI-ready, including semantic layers, knowledge graphs, and ontologies to ensure trusted, governed and scalable use of enterprise data by AI applications and agents. The successful candidate will combine strong knowledge of AI and modern ...

semantic technology. We care more about what you have built and how you approach a problem than a particular tool stack or formal ontology background. You have built a knowledge graph or another connected data application for analytics, content or AI, and can take an idea from domain conversations ...

level stakeholders and aligning technical outcomes with business valueNice to haveExperience applying AI in drug discovery, safety monitoring or clinical development contextsUnderstanding of biomedical ontologies or knowledge graph applicationsKnowledge of regulatory frameworks (FDA, EMA) and experience with data privacy considerationsBackground in computational biology, biostatistics or related scientific disciplineFamiliarity with federated ...

semantic models, metadata expectations and architecture decision records. Promote consistent information models, data contracts, naming, lineage and contextualization practices, including alignment with enterprise ontology, knowledge-graph and unified namespace approaches where these support approved business outcomes. Establish measures for adoption, reuse, reliability, data quality, service performance, user experience and benefits ...

silos and turning it into knowledge that people and machines can meaningfully understand. Graph and Semantics Engineering are emerging enterprise data technologies that use ontologies, advanced analytics and AI to represent knowledge in expressive and innovative ways. Next-generation AI systems powered by knowledge graphs can help organisations manage complexity ...

complementary patent resource containing chemical structures extracted from patents daily. UniChem links chemical structures across databases. ChEBI is a highly curated database and ontology of compounds of biological interest. OPSIN converts systematic chemical names into chemical structures. The EBI is part of the European Molecular Biology Laboratory (EMBL ...

agent/LLM evaluation (eval datasets, automated and expert-in-the-loop scoring, regression testing). Experience with API integration, retrieval layers, knowledge graphs, ontologies, or semantic search. Daily use of AI coding agents (Claude Code, GitHub Copilot, Databricks AI Assistant) as the primary mode of development. Preferred Experience Prior ...

ability to explain technical decisions and assess different architectural approaches. Confidence taking ownership of projects and guiding other engineers technically. Experience with knowledge graphs, ontologies, recommendation systems, human-in-the-loop learning or LLM fine-tuning would be particularly interesting. You don't necessarily need to have held an Architect ...

reliable knowledge and controls, and able to point to at least one hands-on AI-related example. Ideally brings familiarity with knowledge structures (ontologies, taxonomies, knowledge graphs), human–AI interaction or agent design, and measuring business value and governance impacts.Reply is an Equal Opportunities Employer and committed to embracing diversity ...

data, AI and process challenges into scalable Foundry applications. Key responsibilitiesAct as lead architect for Foundry, owning solution design from ingestion and pipelines through Ontology, applications and AI use cases. Translate business problems into Foundry use cases, technical designs and deliverable roadmaps. Design and oversee data pipelines, Ontology models, security … Skills and experienceSignificant hands-on experience delivering Palantir Foundry solutions in complex client environments. Deep Foundry technical expertise across the full stack: Pipeline Builder, Ontology, Workshop, OSDK, Code Repositories, Actions and AIP or agentic capabilities, able to build production-grade applications not just prototypes. Strong proficiency in at least ...

analytics is built here: governed metric definitions and a shared semantic layer so numbers agree across the business, a well-maintained data catalog and ontology so data assets are discoverable and trusted, version control, testing, and documentation as normal practice, and AI used as a core, everyday part … measured properly rather than assumed to have workedStandards and qualityOwn governed metric definitions, a shared semantic layer, the data catalog, and the wider data ontology, ensuring the same question gets the same answer wherever it's asked, data assets are findable and trusted, and metadata, lineage, and business definitions stay ...

works with product teams, R&D partners and manufacturing technology teams to define practical strategies for connecting data and systems (including the use of ontologies, knowledge graphs, integrations and AI where appropriate), enabling more seamless reuse of product and process knowledge across platforms. They also help define and operate … maintain pipelines, automate deployments, manage repositories and environments and ensure changes follow validation and change-control requirements. Work with R&D and central ontology/knowledge-graph teams to implement and operate data and metadata structures (for example applying agreed ontologies, reference data and mappings) so digital product profile data ...

enable the collection, integration, management and exploitation of research and manufacturing data. Working as part of a team, they will develop semantic information models, ontologies and knowledge graph approaches that improve interoperability across digital and physical systems, supporting data-driven decision making and the deployment of advanced digital technologies. Working ...

frontiers of knowledge. You will work with vast, complex, and heterogeneous data - from scientific publications and raw research datasets to biomedical content, citations, metadata, ontologies, taxonomies, knowledge graphs, multilingual content, and domain-specific data across the full spectrum of scientific disciplines. This is AI with purpose: helping researchers advance science … agentic workflows, and scientific knowledge discovery systems. Build and optimise intelligent research and decision-support capabilities using embeddings, retrieval pipelines, prompt engineering, knowledge graphs, ontologies, citation networks, and domain-specific scientific content. Establish robust evaluation, experimentation, and monitoring frameworks for AI and search systems, covering relevance, grounding, hallucination detection, model ...

hands-on role: you will work in code and modelling tools every day, use AI assistants to work faster, and partner with research, ontology and data platform teams as well as external partners. We value curiosity, attention to detail, and a positive mindset. This role offers you the chance … with database technologies and data integration concepts. - Ability to write clear documentation and communicate with technical and non-technical colleagues. - Working knowledge of biomedical ontologies and standards such as NClt, MONDO, EFO, GO, ChEBI, CDISCPreferred Qualification If you have the following characteristics, it would be a plus: - Understanding of data ...

products centered on entity resolution, symbology and knowledge graph capabilities, and you will work close to the detail. That means defining data models and ontologies, writing requirements, working through data quality problems, validating solutions with engineering and getting capabilities into production. You will lead through influence rather than line management. … identifier mapping, corporate hierarchies and ownership, and the knowledge graph that connects them. Get hands-on with the data. Define entity and relationship models, ontologies and metadata standards; profile and investigate data; shape matching and linkage logic; and write detailed requirements and acceptance criteria. Build deep expertise in Fitch ...

term AI engineering capability. As client demand for AI-native transformation accelerates, the consulting practice is expanding its engineering capability across agentic systems, retrieval, ontologies and AI-enabled execution. The Consulting Engineer is a hands-on AI systems builder who combines deep engineering craft with commercial and product thinking … design, build and deploy agentic, retrieval and ontology-based systems for enterprise clients. You will work directly with senior client stakeholders and alongside consulting and orchestration roles, translating complex business challenges into safe, reliable and measurable AI solutions. Key AccountabilitiesClient-Facing AI Engineering & Agentic System DesignYou will design and deliver ...