Principal Machine Learning Engineer

Overview

Asos seeks a Principal Machine Learning Engineer to steer the technical direction of AI-powered fashion discovery. You will define architecture for large-scale ML systems spanning recommendations, search relevance and conversational experiences, aligning with the Search & Discovery mission. You’ll mentor engineers, drive engineering excellence, and shape scalable, production-grade ML platforms. This role offers impact across customer journeys and product experiences, with a chance to influence strategic tech choices at scale.

Pay / Benefits

• Employee discount
• Employee sample sales
• 25 days paid annual leave
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance

Responsibilities

• Own end-to-end technical architecture for ML systems powering personalised fashion experiences
• Lead design and evolution of large-scale batch and real-time ML systems serving millions
• Drive cross-team architectural decisions for scalability and reliability
• Set technical direction across recommendation, retrieval, personalisation, search relevance, DL and generative AI
• Provide technical leadership and mentorship to senior staff while promoting best practices
• Translate research into production-ready ML products and address lifecycle challenges
• Represent the engineering function in discussions with senior stakeholders and business leaders
• Contribute to technical standards and engineering best practices across teams
• Drive development of shared ML capabilities and tooling across Search & Discovery

Key requirements

• Extensive experience designing, building and operating large-scale ML systems in production
• Experience owning and influencing technical architecture across complex ecosystems
• Product-focused mindset applying ML/AI to business challenges
• Experience across ML lifecycle: data analysis, feature engineering, model development, evaluation, deployment, monitoring
• Experience building scalable, observable ML services using cloud-based and distributed infrastructure
• Two or more areas of deep expertise: ranking/relevance, recommendation systems, DL, LLMs, IR, NLP or content understanding
• Advanced hands-on with PyTorch, TensorFlow or similar frameworks
• Strong Python and/or Java/C++ programming skills
• Deep understanding of MLOps: deployment, observability, monitoring, lifecycle at scale
• Experience with retrieval-augmented generation (RAG), agent-based architectures, retrieval systems, model evaluation frameworks
• Experience using AI-assisted engineering tools and coding agents (e.g., Claude Code, Codex, Cursor) throughout SDLC

• leadership
• strong communication
• stakeholder management
• PyTorch
• TensorFlow
• Python

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