Senior Machine Learning Engineer (Recommendations/Search)

Overview

As Senior Machine Learning Engineer, you will design, build and operate production ML systems powering outfit discovery and personalised fashion experiences. You will work within the Search & Discovery team to deploy models that affect millions of customers, collaborating with ML Scientists and engineers to scale AI-powered features. You’ll improve performance, reliability and observability of ML pipelines, while shaping technical practices and mentoring peers. This role offers the chance to influence how customers find styles and outfits through AI-driven experiences.

Pay / Benefits

• Employee 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 fashion experiences
• Collaborate with ML Scientists to deploy deep learning models and deliver business outcomes
• Deploy and optimise batch and real-time ML models serving millions of customers
• Contribute to systems powering recommendations, personalisation and AI-driven 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
• 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 software engineering practices
• Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow or similar
• Experience training and optimising models with large datasets and distributed compute infrastructure
• Experience working with recommendation systems, ranking, retrieval, personalisation or related ML domains
• Knowledge of MLOps including model deployment, monitoring and lifecycle management
• Experience building reliable, observable and scalable services in cloud environments
• Comfortable providing technical leadership and mentoring other engineers
• Strong collaboration and communication skills in cross-functional product teams
• Curiosity about emerging AI technologies and practical applications of LLMs and generative AI in customer-facing products

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

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