About the job

Neurolabs is seeking a Lead Computer Vision Engineer to spearhead its mission of revolutionising retail execution through advanced Image Recognition technology powered by synthetic data and digital twins, enabling global CPG brands to gain immediate, scalable, and accurate visibility into in-store performance without the delays of manual audits or retraining. In this high-impact leadership role, you will manage and mentor a small but highly skilled ML team, setting clear goals, driving sprint rhythms, prioritising multiple projects, and unblocking technical challenges while maintaining a healthy, collaborative, and outcome-driven environment. You will own and evolve the technical roadmap for computer vision models and systems, balancing short-term delivery with long-term scalability, and contribute directly to architectural decisions, model refinement, optimisation, and experimentation with large vision models and multimodal approaches. The role demands strong expertise in Python, PyTorch or TensorFlow, deep knowledge of computer vision pipelines, MLOps practices, cloud infrastructure like AWS or GCP, and experience taking models from research to production in real-world, data-constrained environments. A people-first approach is essential, as you will collaborate closely with staff-level engineers, product and infrastructure teams, and business stakeholders to turn commercial requirements into robust AI solutions while fostering a culture of curiosity, trust, and continuous learning. Neurolabs offers a competitive salary of up to £130,000 per year, equity share options, hybrid working from its London office near King’s Cross, 25 days of annual leave plus bank holidays, comprehensive private medical insurance including dental and optical cover, company retreats, and a culture of inclusivity and openness. Importantly, visa sponsorship under the UK Skilled Worker route is available for qualified candidates, making this role an exceptional opportunity for ambitious professionals to grow their leadership career in computer vision while contributing to meaningful, cutting-edge innovations that are scaling globally.