Machine Learning Engineer

Description

The company is looking for a Machine Learning Engineer for its Search and Recommendations team, which builds machine learning systems that help millions of customers find products every day.

The team's work covers personalised recommendations, product ranking and newer AI-powered styling features, and it shapes how customers browse and buy.

The ranking and recommendation systems behind features such as Similar Items and People Also Viewed adapt in real time to customer behaviour and process signals from millions of interactions.

You will cover the whole machine learning lifecycle, from experiments and model building through deployment, monitoring and tuning in production. You will work with Machine Learning Engineers, Applied Scientists, Software Engineers and Product partners to turn ideas into reliable, scalable systems with measurable customer and business results.

You will also help shape the team's direction in areas such as next-generation recommendation systems, sequence-based modelling, outfit generation and AI-driven styling.

Responsibilities

• Design, build and maintain production-grade machine learning systems for personalisation and product discovery.
• Develop and improve recommender systems, ranking models and customer-facing machine learning features.
• Deploy models in batch and real-time environments, keeping them reliable, scalable and performant at scale.
• Work with Applied Scientists and Engineers to move models from experimentation into robust production systems.
• Monitor and evaluate models using real customer behaviour and performance metrics, and iterate on them.
• Contribute to engineering best practices, MLOps tooling and shared machine learning platform capabilities.
• Help improve how machine learning is built, deployed and run across the organisation.

Requirements

• Experience developing, deploying or operating machine learning solutions in production.
• Familiarity with modern machine learning frameworks and tools such as PyTorch, TensorFlow, XGBoost or similar.
• Experience training models on GPUs, or an interest in distributed computing and scalable machine learning systems.
• Understanding of software engineering fundamentals: version control, CI/CD, testing, observability and containerisation.
• An appreciation of MLOps practices and the challenges of deploying machine learning systems at scale.
• Strong collaboration and communication skills, with experience working across engineering, science and product.
• Curiosity, adaptability and a real drive to learn new technologies and approaches.
• You are keen to solve real-world problems, learn from others and build systems that have meaningful impact.
• You do not need to meet every requirement to apply.

Conditions

Equal opportunity: candidates are welcome to ask the Talent team for adjustments at any stage of the process.

Benefits

• Employee discount on the company's products.
• Employee sample sales.
• 25 days paid annual leave, plus an extra celebration day for a special moment.
• Private medical care scheme.
• Fixed Annual Payment on top of your salary each year.
• Opportunities for personalised learning and in-the-moment experiences to help you grow in your role.