Machine Learning Engineer

We’re Kingfisher, a team made up of over 74,000 passionate people who bring Kingfisher - and all our other brands: B&Q, Screwfix, Brico Depot, Castorama and Koctas to life. Guided by our purpose Better Homes. Better Lives. For Everyone. We believe a better world starts with better homes, and we work every day to make that a reality. Join us and help shape the future of home improvement. This is an opportunity to make a significant impact across one of the largest retail groups in Europe.

We are looking for a Machine Learning Engineer who will support the delivery and operationalisation of advanced artificial intelligence solutions created by our Group AI team. Your work will help shape how millions of customers and colleagues experience our products, services and decision making across our retail brands. You will work as part of a high performing engineering team to build scalable machine learning systems, ensuring models are robust, efficient and suitable for a live environment. You will collaborate with engineering, product and architecture colleagues to improve tools, processes and practices that accelerate the use of artificial intelligence across the organisation.

Key Accountabilities / Responsibilities

• Develop machine learning models and support their deployment into production
• Write production quality code that is robust, efficient and maintainable
• Contribute to the implementation and improvement of pipelines, tooling and automation
• Apply good engineering standards and practices in model development
• Monitor performance and contribute to ongoing optimisation of models
• Work with colleagues to understand requirements and priorities
• Share knowledge, contribute ideas and support a collaborative team culture

Qualifications

• Good understanding of computer science fundamentals, including data structures, algorithms and software design
• Practical experience with classical machine learning techniques and an awareness of modern approaches such as natural language processing and deep learning
• Strong Python skills and experience with common libraries such as Pandas, scikit-learn and Jupyter
• Experience working with SQL and data pipelines to prepare and transform data for model training
• Understanding of model evaluation, monitoring and improving performance in a production environment
• Familiarity with tools and practices for deploying models, ideally including Git, CI workflows and containerisation
• Comfortable working with statistical concepts to interpret data and assess model performance
• Ability to work collaboratively, communicate clearly and deliver work to agreed outcome

How We Work

We believe in flexibility and balance. Our hybrid model blends home working for focus with time spent connecting and collaborating - whether in our offices or at offsite locations. On average within our Engineering team, 40% of your time involves in-person collaboration.

What We Offer

An inclusive environment where your potential is limited only by your imagination. We encourage new ideas, support experimentation, and strive to create a workplace where everyone can be their best self. We also offer a competitive benefits package and plenty of opportunities to stretch and grow your career.

Diversity & Inclusion

Our customers come from all walks of life—and so do we. We’re committed to ensuring all colleagues, future colleagues, and applicants are treated equally, regardless of age, gender, marital or civil partnership status, ethnicity, culture, religion, belief, political opinion, disability, gender identity, gender expression, or sexual orientation.

Interested? Great, apply now and help us to Power the Possible.