Senior Machine Learning Engineer (Personalisation)

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

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