Principal ML Engineer — AI-Driven Fashion Discovery

SmartRecruiters, Inc.; Greater London; Hybrid; GBP 120,000 - 190,000; Full time

Benefits offered by this job

25 days PTO

Discretionary bonus

Private medical care

Flexible benefits

Learning & development

Job summary

ASOS, the global fashion retailer, is seeking a Principal Machine Learning Engineer for the Search & Discovery team to shape AI-powered fashion discovery. You will architect large-scale ML systems spanning recommendations, AI Stylist experiences, and personalised product journeys.

You will mentor engineers, drive architectural standards, and collaborate with ML scientists, software engineers and product managers to deliver robust production ML platforms at scale.

Qualifications

• Extensive experience designing, building and operating large-scale ML systems.
• 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, deployment, monitoring.

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.
• Drive cross-team architectural decisions for consistency, scalability and reliability.
• Set technical direction across recommendation, retrieval, personalisation and AI applications.
• Provide technical leadership and mentor senior engineers, promoting engineering excellence.

Skills

ML architecture

Leadership influence

Mentoring

Communication

Tools

PyTorch

TensorFlow

Python

Java

C++

MLOps

RAG

Job description

ASOS, the global fashion retailer, is seeking a Principal Machine Learning Engineer for the Search & Discovery team to shape AI-powered fashion discovery. You will architect large-scale ML systems spanning recommendations, AI Stylist experiences, and personalised product journeys.

You will mentor engineers, drive architectural standards, and collaborate with ML scientists, software engineers and product managers to deliver robust production ML platforms at scale.