Research Engineer - Knowledge Computing / Information Retrieval / LLM
Research Engineer - Knowledge Computing / Information Retrieval / LLM

Research Engineer - Knowledge Computing / Information Retrieval / LLM

Broughton Full-Time 43200 - 72000 £ / year (est.) No home office possible
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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 exciting projects in a collaborative environment with top-tier researchers.

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
Key Requirements:
  • 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
Keywords: Knowledge Graphs / LLMs / Semantic Search / Knowledge Reasoning / NLP / Agent Systems / RAG / OWL / SPARQL / Transformers / Deep Learning / AI Assistants / QA Systems / Pytorch / TensorFlow / Graph Reasoning / Multi-Modal AI / Knowledge Engineering / Research to Production
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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 from top-tier conferences like ACL and NeurIPS to stay updated on cutting-edge technologies that could be beneficial for your role.

✨Tip Number 2

Engage with the community by attending workshops, webinars, or meetups focused on NLP and AI. Networking with professionals in the field can provide insights into the industry and may even lead to referrals or recommendations for the position.

✨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 applied development environment.

✨Tip Number 4

Prepare to discuss how you would translate research into production-ready applications. Think of specific examples from your past experience where you've successfully implemented research findings into practical solutions, as this will be crucial in interviews.

We think you need these skills to ace Research Engineer - Knowledge Computing / Information Retrieval / LLM

PhD in NLP, Machine Learning, Knowledge Engineering, or related fields
Knowledge technologies (RDF, SPARQL, OWL, SKOS)
NLP (LLMs, entity detection, question answering, agent systems)
Deep learning (transformers, LSTM, etc.)
Strong coding and software design skills
Experience with knowledge graphs and semantic search
Ability to integrate structured and unstructured knowledge
Collaboration skills in a research and applied development environment
Experience with AI development tools and QA systems
Publications in top-tier conferences (e.g., ACL, NeurIPS, ICML, EMNLP, ICLR, AAAI)
Proficiency in frameworks such as Pytorch and TensorFlow
Understanding of multi-modal AI and knowledge reasoning

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, carefully proofread your documents for any errors. Ensure that your CV and cover letter are well-formatted and easy to read, as this reflects your attention to detail and professionalism.

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

Make sure you can talk confidently about your coding skills and experience with relevant technologies like RDF, SPARQL, and deep learning frameworks such as PyTorch or TensorFlow. Consider preparing a small project or code snippet to demonstrate your abilities.

✨Prepare for Collaborative Scenarios

Since the role involves working closely with engineering teams, think of examples from your past experiences where you successfully collaborated on projects. Be ready to discuss how you handle feedback and integrate ideas from others.

✨Understand the Company’s Vision

Research the world-leading research centre and their current projects. Being able to articulate how your skills and interests align with their goals will show your enthusiasm and commitment to contributing meaningfully to their team.

Research Engineer - Knowledge Computing / Information Retrieval / LLM
European Tech Recruit
Location: Broughton
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  • Research Engineer - Knowledge Computing / Information Retrieval / LLM

    Broughton
    Full-Time
    43200 - 72000 £ / year (est.)
  • E

    European Tech Recruit

    50-100
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