Russell Tobin
Ontologist/Taxonomist
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Knowledge Graph Curator – AI / LLM (Contract) | Fully remote | 6 months contract with possible extension | £39K per annum PAYE
We are partnering with one of the world’s most influential online community platforms to find a Knowledge Graph Curator who will help improve how large-scale content is understood using AI and machine learning. This is a unique opportunity to work at the intersection of data, AI automation, and knowledge modeling, helping build the systems that interpret and structure massive volumes of online conversations.
About the Role
In this role, you will work closely with product, engineering, and data teams to grow and maintain a large-scale Knowledge Graph used to understand organic and paid content across a major social platform. You will act as the human-in-the-loop expert, reviewing and validating AI-generated entities, ensuring accuracy, and helping shape how automated systems interpret complex online discussions.
This position sits within a team focused on building advanced content understanding capabilities powered by applied machine learning and knowledge graphs. The insights generated help improve advertising performance, marketplace intelligence, and large-scale content classification.
Key Responsibilities
Knowledge Graph Curation
- Onboard and maintain entities and relationships within the Knowledge Graph.
- Ensure accurate representation of concepts, entities, and semantic relationships.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
AI-Assisted Data Review
- Review entities generated by Large Language Models (LLMs).
- Approve high-confidence outputs, correct near matches, and reject incorrect data or hallucinations.
Data Labeling & Model Training Support
- Participate in annotation and labeling tasks to improve AI model performance.
- Create high-quality training datasets and “golden sets” used to evaluate model accuracy.
Data Integrity & Quality Assurance
- Identify inconsistencies, duplicates, and errors within the Knowledge Graph.
- Merge duplicate entities and resolve conflicting relationships.
Pipeline & Request Management
- Manage incoming requests from cross-functional teams for new entities or schema updates.
- Prioritize requests based on business impact and urgency.
Stakeholder Collaboration
- Work with product managers, engineers, and analysts to ensure the Knowledge Graph supports business needs.
- Communicate decisions around entity modeling and data structure clearly to non-technical stakeholders.
What We’re Looking For
Knowledge Graph & Data Modeling
- Understanding of graph concepts such as nodes, edges, and properties.
- Experience working with taxonomies, ontologies, or semantic data structures.
Data Literacy
- Comfortable navigating complex datasets.
- Experience with SQL, SPARQL, Cypher, or similar query languages is a plus.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
AI / LLM Familiarity
- Understanding of generative AI concepts and common failure modes such as hallucinations.
- Experience working with data annotation, model evaluation, or AI training pipelines is highly valuable.
Analytical Thinking
- Ability to assess multiple requests and prioritize work that delivers the highest business value.
Attention to Detail
- Strong ability to identify inconsistencies, logical errors, and data quality issues.
Communication Skills
- Comfortable translating technical data concepts into clear explanations for cross-functional teams.
Tools & Environment
You will work with a range of internal tools and data systems, including:
- Knowledge graph platforms
- Data labeling and annotation tools
- Ticketing systems (e.g., Jira)
- Spreadsheet tools such as Excel or Google Sheets
Why This Opportunity?
This role offers the chance to contribute to cutting-edge AI and knowledge graph systems used to interpret and structure massive volumes of online discussion. You’ll help ensure automated systems understand real-world conversations accurately, enabling better insights, recommendations, and advertising performance at scale.
If you enjoy working at the intersection of data quality, AI systems, and knowledge modeling, this could be an exciting next step in your career.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location