Machine Learning Engineer

We're looking for someone who's hands-on, curious, and ready to make a difference. You'll need strong experience in Python especially with the scikit learn ecosystem and MLFlow and be confident working with SQL to manipulate and cleanse large datasets. You'll have a solid understanding of both supervised and unsupervised machine learning techniques, and you'll know how to evaluate and deploy models in a cloud environment. Experience with AI APIs, pretrained open-source models, and tools like Databricks or Azure Cognitive Services will be a big plus. If you've worked on end-to-end Gen AI solutions or have applied ML in retail or ecommerce settings, we definitely want to hear from you.

You'll also need to be a great communicator able to explain complex technical ideas in a clear, compelling way to non-technical stakeholders. And just as importantly, you'll bring a strong ethical mindset, a collaborative spirit, and a genuine enthusiasm for learning and innovation.

So, are you ready to help us unlock the power of AI? If you're looking for a role where you can innovate, collaborate, and see the real-world impact of your work we'd love to hear from you. Join Specsavers and help us build a smarter, more connected future.

We're on a mission to change lives through better sight and hearing and we believe machine learning and AI are key to making that happen. That's why we're looking for a Machine Learning Engineer to join our growing AI & ML Engineering team. If you're excited by the idea of building intelligent solutions that make a real-world impact, this could be the role for you. This is your chance to work on some of the most exciting and forward-thinking projects in the business. You'll be designing and building machine learning models, developing generative AI solutions, and helping us shape the future of AI agents across a global organisation. From supply chain and marketing to clinical and in-store experiences, your work will touch every part of the Specsavers journey. You'll collaborate with data engineers, MLOps specialists, and product owners to bring ideas to life turning complex challenges into smart, scalable solutions.