Machine Learning Engineer - Fully Remote in London

We’re ASOS, the online retailer for fashion lovers all around the world. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions. We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list. Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you. We are seeking a Machine Learning Engineer with a strong foundation in deep learning to join a cross-functional team. You\’ll work closely with data scientists and engineers to deliver impactful machine learning solutions across a wide range of data-rich challenges. Collaborate with cross-functional teams to design, implement, and optimize machine learning models for real-world business use cases. Deploy and maintain both batch and real-time machine learning systems at scale. Work alongside data scientists to translate experimental models into robust production-ready solutions. Contribute to defining team best practices and engineering standards in machine learning development. Stay up to date with the latest industry research and bring new insights to the wider ML community within the business. Hands-on professional experience in developing and deploying machine learning solutions, with a focus on deep learning. Experience working with modern ML frameworks and familiarity with end-to-end deployment workflows. Proficiency in training models using GPUs, and a strong interest in distributed computing and scalable systems. Familiar with software development practices including version control, CI/CD, containerization, and monitoring, especially within ML Ops workflows. Competitive salary and performance-based bonus scheme Generous employee discount and exclusive product access Structured personal and professional development opportunities Paid annual leave plus an additional day for special personal milestones Flexible benefits allowance and private medical care options Access to a variety of online learning resources and employee-led communities