At a Glance
- Tasks: Lead the evolution of a knowledge discovery engine and design scalable search architectures.
- Company: Global expert network platform driving multi-million dollar investment decisions.
- Benefits: Competitive salary, hybrid work model, and direct impact on high-stakes projects.
- Other info: Join a diverse, remote-first team that values collaboration and innovation.
- Why this job: Shape the future of intelligent search and collaborate with top tech teams.
- Qualifications: 5+ years in search systems, expert Python skills, and cloud-native experience.
The predicted salary is between 80000 - 100000 £ per year.
Company Description: Global expert network platform powering multi‑million dollar investment decisions for Private Equity and consulting firms.
You will lead the technical evolution of a knowledge discovery engine, bridging the gap between niche human expertise and intelligent search. By architecting hybrid Graph RAG and GNN systems, you'll enable global investors to surface critical insights from complex, unstructured data, directly impacting high‑stakes strategic decisions and multi‑million dollar deals.
Location: London, UK (Hybrid)
Why this role is remarkable:
- Architect a next‑generation hybrid Graph RAG + GNN reranker system in direct partnership with product teams at Google Cloud.
- Enjoy a high‑impact Staff‑level IC position reporting directly to the CTO with 70% hands‑on technical ownership and zero internal politics.
- Work with a diverse, remote‑first European engineering culture that values low‑ego collaboration and provides access to unique, varied data sets.
What You Will Do:
- Define the future search stack by designing a scalable, cloud‑native architecture combining vector search, hybrid retrieval, and LLM re‑ranking.
- Design and implement a Knowledge Graph architecture to model complex entities and build extraction pipelines using frontier models like GPT‑4 and Gemini.
- Build production‑grade retrieval pipelines and feature stores on GCP using BigQuery, ensuring long‑term scalability, observability, and cost efficiency.
The ideal candidate:
- 5+ years of experience building and scaling production search or retrieval systems with a focus on semantic search and embeddings.
- Proven track record of designing search architectures from first principles and evaluating emerging technologies for commercial use‑cases.
- Expert‑level Python skills and experience building production‑grade LLM applications on cloud‑native infrastructure, preferably Google Cloud Platform.
Search & AI Retrieval Lead (£100k) at Global Expert Network Platform in London employer: Jack & Jill
As a leading global expert network platform based in London, we offer an exceptional work environment that fosters innovation and collaboration. Our hybrid work culture promotes flexibility while providing access to unique data sets and the opportunity to work alongside top-tier talent in the industry. With a focus on employee growth and a commitment to low-ego teamwork, we empower our staff to make impactful contributions to high-stakes investment decisions.
StudySmarter Expert Advice🤫
We think this is how you could land Search & AI Retrieval Lead (£100k) at Global Expert Network Platform in London
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We think you need these skills to ace Search & AI Retrieval Lead (£100k) at Global Expert Network Platform in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jack & Jill. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
