Senior Machine Learning Scientist (Personalisation)

We're looking for a Senior Machine Learning Engineer to join our cross functional Personalisation team. In this role, you'll help design, build and run machine learning systems that enable customers to discover and shop outfits that reflect their personal style as well as current fashion trends. This is a senior individual contributor role where you'll work closely with engineers, data scientists and product partners to productionise machine learning at scale. Our mission is to continuously improve the customer experience through thoughtful, responsible and high impact use of machine learning. What you'll be doing

• Working as part of an agile, cross functional team to build and improve algorithms used in areas such as pricing and customer targeting
• Collaborating with scientists and engineers to implement and deploy machine learning solutions at scale, supporting hundreds of millions of products and customers
• Deploying and maintaining both batch and real time machine learning models in production environments
• Improving and evolving our codebase, tooling and platforms, and contributing to the design of new features and capabilities
• Supporting and mentoring more junior team members, helping them develop their technical skills and confidence
• Contributing to technical direction, helping define machine learning standards, and sharing knowledge across ASOS's wider ML and engineering community
  
  Professional experience applying machine learning in real world, production environments, with a focus on deep learning techniques
• Experience working with recommendation or ranking systems (or a strong interest in this space)
• Familiarity with modern deep learning frameworks and distributed computing approaches for training large scale models
• Experience training models across GPUs using data and/or model parallelism, or enthusiasm to deepen your knowledge in this area
• A solid understanding of software engineering principles, including data pipelines, CI/CD, containerisation and observability, with exposure to MLOps practices and tooling
• Comfortable providing technical guidance, mentoring and support to a small number of less experienced engineers
• Enjoy collaborating across teams and contributing to shared engineering initiatives