Senior Machine Learning Engineer (Personalisation)

Company: ASOS
Apply for the Senior Machine Learning Engineer (Personalisation)
Location: London
Job Description:

Overview

As a Senior Machine Learning Engineer in ASOS’s Search & Recommenders team, you design, build and operate large-scale ML systems that power search, ranking and recommendations used by millions. You’ll collaborate across disciplines to turn ideas into reliable, high-performing production systems with measurable customer and commercial impact. You’ll tackle challenges in personalization and real-time delivery, shaping the future of ML at ASOS.

Pay / Benefits

  • employee discount (hello ASOS discount!)
  • employee sample sales
  • 25 days paid annual leave + an extra celebration day
  • discretionary bonus scheme
  • private medical care scheme
  • flexible benefits allowance

Responsibilities

  • Design, build and improve ML systems powering search, ranking and recommendation experiences
  • Collaborate with Applied Scientists and engineers to deploy ML solutions delivering customer and commercial value
  • Build, deploy and maintain batch and real-time ML models in production
  • Contribute to recommendation, ranking and personalisation capabilities handling millions of interactions daily
  • Continuously improve systems, codebase and engineering practices with new features
  • Support and mentor other engineers through coaching and knowledge sharing
  • Contribute to the team’s technical direction and ML standards across the wider community

Key requirements

  • Experience applying machine learning and deep learning techniques in production
  • Experience with deep learning frameworks and distributed computing for large-scale models
  • Experience with distributed training infrastructure, GPU-based training and parallelisation
  • Strong software engineering fundamentals, development lifecycles and MLOps
  • Experience delivering reliable, scalable ML systems in production
  • Ability to provide technical leadership, mentoring and support to engineers
  • Strong collaboration and communication across engineering, science and product teams
  • collaboration and teamwork
  • communication
  • mentoring and coaching
  • deep learning frameworks
  • distributed computing
  • distributed training infrastructure

…

Posted: October 1st, 2026