At a Glance
- Tasks: Design and develop knowledge models and retrieval systems for cutting-edge intelligence platforms.
- Company: Innovative tech firm focused on transforming information into actionable knowledge.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: High-ownership role with potential for significant career advancement.
- Why this job: Join a small, technical team and make a real impact on foundational intelligence infrastructure.
- Qualifications: Experience in graph databases, information retrieval, and cloud environments preferred.
The predicted salary is between 60000 - 80000 € per year.
We're building a foundational intelligence platform that helps organisations turn fragmented information into durable institutional knowledge, enabling better reasoning, faster decisions, and preserved context over time. Our initial focus is private capital, where information is complex and decisions are high stakes. Longer term, we're building core intelligence infrastructure for any information-led industry.
The Role
As an Applied Research Engineer, you'll own the core knowledge and retrieval infrastructure that everything else builds on. You'll work at the intersection of knowledge representation, information retrieval, and applied NLP, translating research ideas into production systems that reason over real-world, proprietary data. This is a high-ownership role in a small, deeply technical team.
What You'll Work On
- Designing knowledge models and ontologies that preserve semantic meaning and relationships
- Building hybrid retrieval systems (graph, structured, sparse, dense) with contextual understanding and re-ranking
- Developing information extraction pipelines for noisy enterprise documents
- Managing knowledge quality and evolution (provenance, conflict resolution, schema changes)
- Turning research into robust, production grade infrastructure
What We're Looking For
We're especially interested in candidates with experience in one or more of the following areas:
- Graph databases and graph based systems (ideally Neo4j or similar)
- Information retrieval systems, including search, ranking and semantic retrieval
- Enterprise cloud environments, particularly Azure and operating production systems at scale
In addition, you'll likely have:
- A strong background in IR, NLP, knowledge representation, or a related field
- Experience shipping real systems, not just prototypes or research code
- Careful thinking around how information should be structured to support reasoning
- Comfort working from first principles in an early-stage environment
- A high sense of ownership and responsibility for core systems
This Role Is a Good Fit If You:
- Care about the architecture of knowledge, not just model performance
- Enjoy building systems that genuinely understand context, not just embeddings
- Want to influence the technical direction of a core platform
- Value intellectual honesty and pragmatic decision making
- Prefer foundational infrastructure over surface level AI features
Applied Research Engineer (Not Specified) employer: Gold Group Ltd
As an Applied Research Engineer in London, you'll join a pioneering team dedicated to transforming complex information into actionable knowledge. Our hybrid work culture fosters collaboration and innovation, while offering ample opportunities for professional growth in a cutting-edge environment. With a focus on meaningful projects that impact high-stakes decision-making, we provide a unique platform for you to influence the future of intelligence infrastructure.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Research Engineer (Not Specified)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to knowledge representation and information retrieval. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as communication is key in a role like this.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Applied Research Engineer (Not Specified)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in knowledge representation, information retrieval, and applied NLP. We want to see how your skills align with the role of an Applied Research Engineer, so don’t hold back!
Showcase Your Projects:Include specific examples of projects where you've designed knowledge models or built hybrid retrieval systems. We love seeing real-world applications of your work, so share what you’ve done and the impact it had!
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant to the role. Make it easy for us to see why you’re a great fit!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Gold Group Ltd
✨Know Your Stuff
Make sure you brush up on your knowledge of graph databases, information retrieval systems, and NLP. Be ready to discuss how you've applied these in real-world scenarios, as this role is all about turning research into production systems.
✨Show Your Problem-Solving Skills
Prepare to demonstrate your ability to think critically and solve complex problems. Think of examples where you've tackled challenges in knowledge representation or built systems that understand context. This will show your potential employer that you can handle the high-stakes decisions they face.
✨Emphasise Ownership and Responsibility
This role requires a high sense of ownership, so be prepared to talk about times when you've taken charge of projects or systems. Highlight your experience in managing knowledge quality and evolution, and how you've ensured the integrity of core systems.
✨Be Ready for Technical Questions
Expect some deep technical questions during your interview. Brush up on your understanding of hybrid retrieval systems and how to build them. Being able to explain your thought process and the architecture behind your solutions will impress the interviewers.
