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For Companies At a Glance
- Tasks: Join a team to develop intelligent agent systems using cutting-edge AI technologies.
- Company: Work with a world-leading research centre in the UK, focused on innovative AI solutions.
- Benefits: Enjoy a permanent role in Edinburgh with opportunities for impactful work and collaboration.
- Why this job: Make a real-world impact by applying research to AI systems that enhance everyday technology.
- Qualifications: PhD in relevant fields and 3+ years of experience in knowledge technologies or NLP required.
- Other info: Contribute to core algorithm development and engage in a collaborative research environment.
The predicted salary is between 43200 - 72000 £ per year.
We are currently partnered with a world-leading research center in the UK looking to expand their team with a Knowledge Computing Researcher. In this role, you would be working as part of a high calibre team of engineers and researchers to build intelligent agent systems powered by large language models, knowledge graphs, and multi-modal semantic search. This is a unique opportunity to apply cutting-edge research to real-world AI systems with meaningful impact across applications such as intelligent assistants, knowledge-based reasoning, and agent collaboration.
This is a permanent opportunity based onsite in Edinburgh, Scotland.
Key Responsibilities for this Research Engineer position:- Design and implement modules for knowledge-augmented agent systems (retrieval, memory modeling, task orchestration)
- Integrate structured and unstructured knowledge from multiple modalities (text, image, video) into agent workflows
- Develop solutions coupling retrieval (KGs, RAG, databases) with planning, reasoning, and execution logic
- Collaborate with engineering teams on LLM platforms, search infrastructure, and agent systems
- Translate research into production-ready applications across AI development tools, QA systems, and assistant use-cases
- Contribute to core algorithm development and support product scaling initiatives
- PhD in NLP, Machine Learning, Knowledge Engineering, or related fields
- 3+ years of experience in at least one of: Knowledge technologies (RDF, SPARQL, OWL, SKOS); NLP (LLMs, entity detection, question answering, agent systems); Deep learning (transformers, LSTM, etc.)
- 2+ publications in top-tier conferences (e.g., ACL, NeurIPS, ICML, EMNLP, ICLR, AAAI)
- Strong coding and software design skills
- Experience working across research and applied development in a collaborative environment
If you are interested in this Research Engineer position, please send a CV to ts@eu-recruit.com.
Contact Detail:
European Tech Recruit Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer - Knowledge Computing / Information Retrieval / LLM
✨Tip Number 1
Familiarise yourself with the latest advancements in knowledge computing and information retrieval. Follow relevant research papers and publications, especially those from top-tier conferences like ACL and NeurIPS, to understand current trends and challenges in the field.
✨Tip Number 2
Engage with the community by attending workshops, webinars, or meetups focused on NLP and AI technologies. Networking with professionals in the field can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Showcase your coding skills by contributing to open-source projects related to knowledge graphs or LLMs. This not only enhances your portfolio but also demonstrates your ability to work collaboratively in a research and development environment.
✨Tip Number 4
Prepare to discuss how you would translate research into practical applications. Think of examples where you've successfully implemented theoretical concepts into real-world solutions, as this will be crucial in interviews.
We think you need these skills to ace Research Engineer - Knowledge Computing / Information Retrieval / LLM
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in NLP, machine learning, and knowledge engineering. Emphasise your PhD and any publications in top-tier conferences, as these are key requirements for the role.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the responsibilities and requirements listed in the job description. Explain how your skills and experiences align with their needs, particularly in building intelligent agent systems and working with large language models.
Showcase Your Projects: Include details of any projects you've worked on that relate to knowledge graphs, semantic search, or AI assistants. Highlight your coding skills and any collaborative work you've done in research and applied development.
Proofread and Format: Before submitting your application, proofread all documents for spelling and grammatical errors. Ensure your CV and cover letter are well-formatted and easy to read, as this reflects your attention to detail.
How to prepare for a job interview at European Tech Recruit
✨Showcase Your Research Experience
Be prepared to discuss your PhD research and any publications you've contributed to. Highlight how your work relates to knowledge computing, NLP, or LLMs, and be ready to explain complex concepts in a way that's accessible.
✨Demonstrate Technical Proficiency
Since the role requires strong coding and software design skills, brush up on relevant programming languages and frameworks like Python, PyTorch, and TensorFlow. Be ready to discuss specific projects where you've applied these technologies.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Practice solving problems related to knowledge graphs, retrieval systems, and multi-modal AI. Think aloud as you work through these problems to demonstrate your thought process.
✨Emphasise Collaboration Skills
This position involves working closely with engineering teams. Prepare examples of past collaborative projects, focusing on how you contributed to team success and navigated challenges in a research or applied development environment.
