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Machine learning engineer – founding team (computer vision / genai)

Slough
Brio Digital
Machine learning engineer
Posted: 21 June
Offer description

Machine Learning Engineer – Founding Team (Computer Vision / GenAI)


Location: Remote-first (UK-based) | Salary: £50k–£70k + Equity


A well-backed, early-stage startup is building a cutting-edge AI platform that transforms real-world visitor experiences at physical venues — from cultural institutions to entertainment destinations. Following successful pilots with major partners and recent pre-seed investment, we’re scaling up and looking for a Machine Learning Engineer to lead the development of our core AI systems.


What You’ll Work On:


🔹 Computer Vision:

Enable the system to recognise what users are viewing in real time using image embeddings, similarity search (e.g. CLIP, vector search), and traditional CV approaches (e.g. YOLO, MobileNet).


🔹 LLM & RAG Systems:

Design and implement pipelines that support retrieval-augmented generation, internal AI tools, and scalable content delivery. Experience with vector databases, agent frameworks, or data workflows is highly relevant.


🔹 Deployment & MLOps:

Own model deployment pipelines, including API-based serving, monitoring, and cloud infrastructure (AWS preferred, but others welcome). Bonus points for edge/offline deployment experience.


🔹 Product & Strategy:

Work directly with the founder on roadmap decisions, help shape technical direction, and grow into a potential leadership role as the team expands.


About You:

* 2–5+ years of experience in ML/CV/GenAI
* Proficiency in Python, ML frameworks, and cloud-based infrastructure
* Product-focused mindset with a desire to shape early-stage tech
* UK-based and open to occasional travel for testing and collaboration


Why Join:

* Build something novel at the intersection of CV and GenAI
* Be part of the founding team with real influence and equity
* Work remotely with the flexibility to grow your role as we scale
* Backed by strong early traction and funding

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