Lead Data Scientist

Search, Ranking, Retrieval and LLM Modelling

Early Stage AI Company

We are working with a fast growing early stage company that is building a new intelligence layer for the next era of product discovery. With AI assistants becoming the first place consumers turn to for information and recommendations, brands need to understand how these systems interpret products, surface them and prioritise them across different conversational and search environments. This is exactly what this company solves.

They already partner with global consumer brands and now want to hire a Lead Data Scientist to architect and own the modelling engine that powers the platform.

This is a hands-on role with serious technical ownership. You will design and build the systems that identify the signals that matter most for visibility, the retrieval and embedding architecture that feeds the models, the ranking and scoring framework that prioritises actions and the evaluation layer that measures how different LLMs behave across queries, surfaces and contexts.

You will work across ranking signals, vector and semantic representations, entity understanding, graph-based relationships, model serving, observability, cost and latency optimisation, and the connection between unstructured signals and automated recommendations. You will also help shape the long-term ML strategy, including platform design, experimentation frameworks and the future of the discovery engine.

This role suits someone who has experience in search, ranking, retrieval or recommendation systems at scale and who enjoys building practical production models rather than working in isolation. You will work closely with the founder and have real influence over the direction of the product and the future of the intelligence stack.

The package is strong and comes with a competitive base plus bonus and meaningful early-stage equity with genuine upside.

If you are interested in joining a company at a stage where your work will directly shape the product, the system and the category, we would like to speak with you.