Senior Machine Learning Engineer (Recommendations/Search)

Overview

In this role you design, build and operate production ML systems powering outfit discovery and personalised fashion experiences. You work within ASOS’s Search & Discovery team to deploy DL models and deliver meaningful customer and business outcomes. You will deploy scalable batch and real-time models serving millions of customers, shaping AI-powered fashion discovery across the customer journey. You collaborate with ML Scientists, Engineers and Product Managers to advance technical practices and shared ML capabilities, making an impact at scale.

Pay / Benefits

• Employee discount (ASOS)
• Employee sample sales
• 25 days paid annual leave + 1 extra celebration day
• Discretionary bonus scheme
• Private medical care
• Flexible benefits allowance

Responsibilities

• Design, build and operate production machine learning systems that power outfit discovery and personalised fashion experiences
• Collaborate with Machine Learning Scientists to deploy deep learning models and deliver measurable outcomes
• Deploy and optimise batch and real-time ML models serving millions of customers
• Contribute to systems that power recommendations, personalisation and AI-driven fashion discovery across ASOS
• Improve system 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, collaboration and knowledge sharing
• Strengthen technical practices across the team and the wider ML community at ASOS
• Develop shared ML capabilities, tools and best practices used across multiple teams

Key requirements

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

• Collaboration
• Communication
• Mentoring
• PyTorch
• TensorFlow
• MLOps (deployment, monitoring, lifecycle management)

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