Lead Data Scientist, Computer Vision London, UK (Hybrid) | Full-time Help reinvent how the world discovers fashion. We’re building a new era in fashion discovery — one that ignites body confidence in everybody and every body. Imagine Shazam meets Spotify, but for fashion. Our community is tired of endless scrolling, paid ads and dead-end links. They want fashion that actually fits: in stock, in their size, and at the best price. We're creating a search experience that puts people at the centre of discovery. As a female-founded fashion-tech startup, we're at an exciting stage — shaping something genuinely game-changing. Now we’re looking for an exceptional Lead Data Scientist (Computer Vision) to help build the intelligence at the heart of our platform. The Role This is a hands-on technical leadership role responsible for architecting and building the computer vision engine powering the platform’s discovery experience. You’ll design, implement and productionise state-of-the-art models across image understanding, embeddings, object detection and emerging agentic AI systems. You’ll work closely with the founders, product and engineering teams to shape the long-term AI and data strategy, making pragmatic technical decisions in a fast-moving startup environment. ⚠️ This role is 90% hands-on engineering. It is not a pure management role or a research-only position. What You’ll Do Hands-on Computer Vision Leadership Design, build and deploy production computer vision and agentic AI systems powering search, recommendations and personalisation Own the full data science lifecycle: problem framing → modelling → deployment → monitoring → iteration Make pragmatic trade-offs between speed, quality and technical elegance Product & User Impact Translate messy real-world user problems into testable ML solutions Partner closely with Product to ensure models improve user trust, confidence and discovery Focus on feature value, ROI and the signals that truly matter Data Foundations Work hands-on with imperfect datasets Design annotation strategies, data quality frameworks and evaluation pipelines Decide where data investment matters most Technical Direction & MLOps Establish pragmatic MLOps practices (deployment, monitoring, iteration) Build scalable but lightweight ML pipelines in AWS alongside engineering Ensure models are robust, reliable and safe for production Team & Culture Set the technical bar for data science Mentor future data scientists as the team grows Bring curiosity, humility and ownership to a high-ambiguity startup environment ✅ What We’re Looking For Bachelor’s or Master’s in Computer Science, Mathematics or related field Strong computer vision expertise and experience fine-tuning state-of-the-art models Deep learning experience (e.g. PyTorch, CUDA, model optimisation for training and inference) Strong MLOps and engineering mindset (CI/CD, automated deployment, monitoring) Solid understanding of data engineering, data quality and annotation strategies Comfortable working in fast-paced startup environments A simplicity-first mindset — only introduce complexity when it’s needed Excellent communication skills across technical and non-technical audiences Why Join? Build the core AI engine of a breakthrough fashion discovery platform Work directly with founders on product and technical strategy Join a mission-driven, female-founded startup at a defining growth stage Shape a product designed to make fashion discovery more inclusive, empowering and intelligent Interested? We’d love to hear from exceptional builders who want to shape the future of fashion discovery. Apply via LinkedIn or reach out directly.