Senior Machine Learning Engineer; Customer​/Marketing

We're ASOS. We blend our flair for fashion with our love of cutting- edge technology, but more importantly were interested in how we can bring the best out of you.

We exist to give people the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you're free to be your true self without judgment, and channel your creativity into a platform used by millions.

At ASOS, machine learning is a core part of how millions of customers discover products, engage with our brand and shop every day.

We're looking for a Senior Machine Learning Engineer to join our Customer & Martech team. In this role, you'll help build and scale machine learning products that support customer growth, marketing effectiveness, pricing and personalisation.

You will work with some of ASOS's richest datasets, including customer behaviour, transactions, marketing interactions and product data, turning these into production-grade machine learning systems that deliver measurable value for customers and the business.

Working alongside Applied Scientists, Data Engineers and Machine Learning Engineers, you'll contribute across the full lifecycle of machine learning products, from ideation and experimentation through to deployment, monitoring and optimisation.

Whether improving customer retention, optimising marketing investment, supporting intelligent pricing decisions or helping build the next generation of customer experiences, you'll work on complex challenges at significant scale.

• Design, build and operate machine learning systems that support customer engagement, marketing effectiveness, pricing and commercial decision-making.
• Own the end-to-end engineering lifecycle of machine learning products, including data ingestion, feature engineering, deployment, monitoring and optimisation.
• Product ionise advanced machine learning solutions and ensure they operate reliably at ASOS scale.
• Partner closely with Applied Scientists to translate research and experimentation into scalable production systems.
• Help shape the future of our MLOps platform by contributing to engineering best practices, operational excellence and platform capabilities.
• Build reusable tooling, frameworks and infrastructure that accelerate machine learning delivery and reduce operational overhead.
• Influence technical direction and architectural decisions across machine learning products and platforms.
• Mentor colleagues and support high standards of engineering quality, reliability and scalability.

This is an opportunity to work on machine learning products used by millions of customers, leveraging rich datasets across customer behaviour, marketing, pricing and ecommerce. You'll collaborate with Applied Scientists, Machine Learning Engineers and Data Engineers to solve complex challenges at the intersection of machine learning, software engineering and large-scale data systems, while seeing the direct impact of your work on customer experience and commercial outcomes.

You'll also help shape the future of ASOS's machine learning platform and engineering standards in an environment where machine learning is a core business capability.

We recognise that people may not meet every requirement listed above. If your experience is relevant to the role and you believe you could contribute to the team, we encourage you to apply.

• Experience building, deploying and operating machine learning systems in production environments.
• Strong software engineering fundamentals, including expertise in Python and modern engineering practices.
• Experience building scalable batch and real-time machine learning pipelines in cloud environments.
• Strong understanding of MLOps principles, including model deployment, monitoring, CI/CD, observability and operational excellence.
• Experience working with large-scale data processing technologies such as Spark.
• Strong understanding of machine learning frameworks such as PyTorch, Tensor Flow, XGBoost or similar technologies.
• Experience designing reliable APIs, services and platforms that support machine-learning-powered products.
• Ability to work through ambiguity and lead complex technical initiatives.
• Experience in customer intelligence, marketing optimisation, pricing, forecasting or personalisation.
• Experience building feature platforms, ML platforms or shared machine learning infrastructure.
• Exposure to experimentation frameworks, causal inference or measurement platforms.
• Experience mentoring engineers and influencing technical direction beyond your…