Principal Machine Learning Engineer

Description

The team is hiring a principal engineer for its Search and Discovery group to set the technical direction for AI-driven fashion discovery.

The company is an online fashion retailer. Its Search and Discovery group combines recommendations, personalisation, deep learning and large language model work to help millions of shoppers find outfits that suit their taste and current trends.

You will shape the architecture of large-scale systems covering personalised product and outfit recommendations, a conversational styling assistant, search relevance, style discovery and other product features across the shopping journey.

You will work with machine learning scientists, software engineers, engineering leaders and product managers, leading technically across the group while staying hands-on with architecture, system design and engineering choices.

The role carries wide influence over how machine learning engineering is done at the company, including mentoring others and raising engineering standards across the organisation.

Responsibilities

• Own the end-to-end architecture of machine learning systems behind personalised fashion experiences, including outfit discovery, homepage ranking and the styling assistant.
• Lead the design and evolution of large batch and real-time machine learning systems used by millions of customers.
• Make architecture decisions across teams so systems stay consistent, scalable, reliable and easy to maintain.
• Set the long-term technical direction for recommendation, retrieval and AI-powered discovery platforms.
• Set technical direction and best practices for recommendation, retrieval, personalisation, search relevance, deep learning and generative AI work.
• Work with scientists and engineering leaders to turn research and experiments into robust production systems.
• Find and fix architecture, scalability, reliability and performance problems across the machine learning lifecycle.
• Help deliver production-grade customer-facing ML products that create measurable business and customer value.
• Lead strategic initiatives, including platform investment decisions and build-or-buy evaluations.
• Mentor senior and staff engineers and help grow engineering capability across the organisation.
• Promote engineering excellence, modern software practices and responsible use of AI-assisted development tools.
• Contribute to technical standards, architectural principles and engineering best practices across several teams.
• Drive the building of shared machine learning capabilities, tools and frameworks used across the group and wider engineering.
• Represent the group's engineering in discussions with senior stakeholders, technology partners and business leaders.
• Explain technical strategy, trade-offs and outcomes clearly to both technical and non-technical audiences.

Requirements

• Show significant experience with a number of the areas listed below. Expertise may have been built through different career paths.
• Have extensive experience designing, building and running large-scale machine learning systems in production.
• Have owned and influenced technical architecture across complex engineering environments.
• Bring a product mindset and enjoy applying machine learning and AI to customer and business problems.
• Have extensive experience across the full machine learning lifecycle: data analysis, feature engineering, model development, evaluation, deployment, monitoring and ongoing improvement.
• Have built scalable, observable and highly reliable machine learning services on cloud platforms, distributed infrastructure and large datasets.
• Have deep expertise in at least two of: ranking and relevance, recommendation systems, deep learning, large language models, information retrieval, natural language processing or content understanding.
• Have advanced hands-on experience with PyTorch, TensorFlow or similar machine learning frameworks.
• Program well in Python and/or other languages such as Java or C++.
• Understand MLOps deeply, including deployment, observability, monitoring and lifecycle management at scale.
• Have built production AI systems using methods such as retrieval-augmented generation (RAG), agent-based architectures, retrieval systems, model evaluation frameworks and ML-driven scoring.
• Have significant experience using AI-assisted engineering tools and coding agents, such as Claude Code, Codex, Cursor or similar, across the software development lifecycle.
• Can set out a convincing technical vision and influence several teams without managing them directly.
• Have set architectural direction, driven engineering strategy and encouraged adoption of technical standards across teams.
• Have mentored senior engineers and supported wider engineering development.
• Communicate well and manage stakeholders, including senior technical and business leaders.

Conditions

Equal opportunity: the company welcomes applications from all backgrounds.

The company is a Disability Confident Committed employer, so tell the talent team if you need reasonable adjustments during recruitment.

Benefits

• Employee discount on company products.
• Access to employee sample sales.
• 25 days of paid annual leave, plus an extra day to celebrate a special occasion.
• Discretionary bonus scheme.
• Private medical care scheme.
• Flexible benefits allowance, which you can take as extra cash or spend on other benefits.
• Personalised learning and development opportunities to help you do well in your role.