Machine Learning Engineer

Company: ASOS
Apply for the Machine Learning Engineer
Location: London
Job Description:

Overview

In ASOS’s Search & Recommendations team, you will design and operate production-grade ML systems that power personalised product discovery at scale. You’ll partner with engineers, scientists and product teams to turn ideas into reliable, scalable models that impact customer experience and commercial results. Expect to work across the full ML lifecycle—from experimentation to deployment and monitoring—in a fast-growing retail platform. This role offers the chance to shape future discovery technologies, including next-gen recommender approaches and AI-driven styling experiences.

Pay / Benefits

  • employee discount (hello ASOS discount!)
  • employee sample sales
  • 25 days paid annual leave + extra celebration day
  • private medical care scheme
  • fixed Annual Payment
  • personalised learning opportunities

Responsibilities

  • Design, build and maintain production-grade ML systems for personalisation and discovery
  • Develop and improve recommender and ranking models
  • Deploy models in batch and real-time environments with reliability and scalability
  • Collaborate with Applied Scientists and Engineers to move models from experimentation to production
  • Monitor and iterate on models using real user data and metrics
  • Contribute to ML engineering best practices and platform capabilities
  • Improve ML development, deployment and operations across the organisation

Key requirements

  • Experience delivering or operating ML solutions in production
  • Familiarity with PyTorch, TensorFlow, XGBoost or equivalent
  • Experience training models using GPUs or interest in distributed ML systems
  • Understanding of software engineering fundamentals (version control, CI/CD, testing, observability, containers)
  • Appreciation of MLOps and deploying ML systems at scale
  • Strong collaboration and communication across engineering, science and product
  • Curiosity and ability to learn new technologies
  • collaboration
  • communication
  • curiosity
  • production ML systems
  • recommender systems
  • ranking models

…

Posted: September 21st, 2026