Machine Learning Engineer

We’re looking for a Machine Learning Engineer with an interest or background in machine learning and deep learning to join a collaborative, cross‑functional team. You’ll work closely with data scientists and engineers to build and improve machine learning solutions across a range of data‑rich use cases, with a current focus on recommender systems . Your work will help shape customer experiences across areas such as personalisation and pricing. This role offers the opportunity to contribute to production machine learning systems while continuing to develop your skills in model deployment, scalability, and engineering best practices. What you'll be doing Working with cross‑functional partners to design, build, and improve machine learning models for real‑world business problems, particularly recommender systems Helping to deploy and support batch and real‑time machine learning solutions Collaborating with data scientists to move models from experimentation into reliable, production‑ready systems Monitoring and improving model performance, system efficiency, and reliability Contributing to shared engineering standards, tools, and best practices within the team Keeping up to date with developments in machine learning and sharing relevant insights with the wider ML community at ASOS

About You We’re keen to hear from Machine Learning Engineers who enjoy learning, collaboration, and building practical solutions. You don’t need to meet every requirement below to apply - if the role sounds like a good fit for your experience or career direction, we’d encourage you to apply. Experience contributing to the development or deployment of machine learning solutions Familiarity with modern machine learning frameworks and model deployment workflows Experience training models using GPUs, or an interest in distributed and scalable systems Understanding of software engineering practices such as version control, CI/CD, containerisation, and monitoring, particularly within ML or MLOps contexts A collaborative working style, with clear communication and comfort working across disciplines A willingness to learn, share knowledge, and grow in a supportive, fast‑moving environment

BeneFITS’  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 A supportive, inclusive, and dynamic workplace where innovation thrives