Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy.

They’ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert tagged images. Now, they’re scaling globally — and need a world-class Lead AI Engineer to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges.

Role Overview

They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions.

Key Responsibilities

· Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning)

· Fine-tune, evaluate, and productionise multi-modal LLMs for business applications.

· Drive experimentation and prototyping of advanced ML/AI techniques

· Provide technical direction, mentoring, and hands-on guidance to the data science team.

· Work with engineering, product, and business stakeholders to align ML strategy with business goals.

· Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models.

Requirements
• Strong, current Python, including building and maintaining production services with FastAPI or similar.
• Solid machine learning and computer vision background, with real models shipped to 
production rather than only notebooks and prototypes.
• Hands-on experience with a computer vision training and labelling toolchain such as Roboflow, 
including dataset management and model evaluation.
• Experience with Azure AI services such as Azure AI Foundry and Azure OpenAI, or a clear track 
record on an equivalent cloud AI stack and the ability to pick ours up quickly.
• Practical understanding of working in a regulated or compliance-sensitive environment: data 
residency, de-identification, model governance, auditability, and why explainability matters.
• The judgment to scope and lock a problem before building it, and to know when a model is good enough to ship.
• OpenCV and classical computer vision alongside deep learning.

ALL APPLICANTS MUST BE FREE TO WORK IN THE UK
Exposed Solutions is acting as an employment agency to this client.
Please note that no terminology in this advert is intended to discriminate on any grounds, and we confirm that we will gladly accept applications from any person for this role.