Senior Machine Learning Engineer (Recommendations/Search)

Overview

As Senior Machine Learning Engineer in ASOS’s Search & Discovery, you design, build and operate large-scale ML systems that power personalised outfit discovery and fashion experiences. You work with ML Scientists and engineers to deploy models and optimize serving for millions of customers. You help shape scalable data-driven solutions across recommendations and AI-driven fashion discovery. This role offers impact on product experience and the chance to advance ML at scale.

Pay / Benefits

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

Responsibilities

• Design, build and operate production ML systems powering outfit discovery and personalised experiences
• Collaborate with ML Scientists to deploy deep learning models and drive business outcomes
• Deploy and optimise batch and real-time models serving millions of customers
• Contribute to systems powering recommendations, personalisation and AI-driven fashion discovery
• Improve performance, reliability, observability and scalability across the ML lifecycle
• Contribute to technical design decisions, architecture discussions and engineering best practices
• Mentor and support other engineers through coaching and knowledge sharing
• Strengthen technical practices across the team and the wider ML community at ASOS
• Contribute to shared ML capabilities, tools and best practices used across multiple teams

Key requirements

• Experience designing, building and deploying ML systems in production
• Strong understanding of ML engineering principles and modern software engineering practices
• Hands-on experience with PyTorch, TensorFlow or similar
• Experience training and optimising models with large datasets and distributed compute
• Experience working with recommendation systems, ranking, retrieval, personalisation or related ML domains
• Knowledge of MLOps practices including deployment, monitoring and lifecycle management
• Experience building reliable, observable and scalable cloud services
• Ability to provide technical leadership and mentoring
• Strong collaboration and communication skills in cross-functional teams
• Curiosity about emerging AI technologies and practical application of LLMs and generative AI in customer products

• collaboration
• communication
• mentoring
• PyTorch
• TensorFlow
• large-scale ML training

…