Senior Machine Learning Engineer

We're looking for a Senior Machine Learning Engineer to join our cross-functional Outfits Discovery team, where we're building the next generation of AI-powered fashion experiences at ASOS. Our mission is to help millions of customers discover complete outfits that match their personal style, preferences and the latest fashion trends. We develop large-scale machine learning systems that power personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey. As a Senior Machine Learning Engineer, you'll play a key role in designing, building and operating production machine learning systems at scale. Working alongside Machine Learning Scientists, Software Engineers and Product Managers, you'll help turn cutting-edge research into robust, customer-facing solutions that drive measurable impact for both our customers and the business. This is an opportunity to work on challenging problems spanning recommendation systems, deep learning, personalisation and large-scale inference, while helping shape the technical direction of machine learning across ASOS. What you'll be doing:

• Designing, building and operating production-grade machine learning systems that power outfit discovery and personalised fashion experiences.
• Partnering with Machine Learning Scientists to productionise deep learning models and deliver measurable customer and business impact.
• Deploying and optimising batch and real-time machine learning models that serve millions of customers at scale.
• Driving improvements in system performance, reliability, observability and scalability across the machine learning lifecycle.
• Taking ownership of technical design decisions and contributing to the team's architecture, standards and engineering practices.
• Mentoring and supporting other engineers, helping raise the technical bar across the team and wider machine learning community at ASOS.
• Contributing to the development of shared machine learning capabilities, tools and best practices used across multiple teams.