Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer

Kingfisher
City of London
2 weeks ago
Create job alert
Overview

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. That's right, we're big, but we have ambitions to become even bigger and even better. We want to become the leading home improvement company and grow the largest community of home improvers in the world. And that's where you come in.


At Kingfisher our customers come from all walks of life, and so do we. We want to ensure that all colleagues, future colleagues, and applicants to Kingfisher are treated equally regardless of age, gender, marital or civil partnership status, colour, ethnic or national origin, culture, religious belief, philosophical belief, political opinion, disability, gender identity, gender expression or sexual orientation.


We are open to flexible and agile working, both of hours and location. Therefore, we offer colleagues a blend of working from home and our offices, located in London, Southampton & Yeovil. Talk to us about how we can best support you!


We are looking for a Machine Learning Engineer to join our growing team, to develop and deploy core ML/AI algorithms required to tackle data science challenges across Kingfisher Group. You will support data science projects from start to production, developing quality code and carrying out automated build and deployments, working closely with colleagues in the Data Science team as well as stakeholders across the business.


Responsibilities

  • Develop high-quality machine learning models to solve business challenges
  • Develop production quality code and carry out basic automated builds and deployments
  • Write comprehensive, well written documentation that meets our needs
  • Identify work and dependencies, tracking progress through a set of tasks
  • Communicate clearly with colleagues and business stakeholders
  • Proactively share ideas with colleagues and accept suggestions
  • Ability to work on multiple data science projects and manage deliverables

What you'll bring

  • Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture
  • Solid understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc), state-of-the-art research area (e.g. NLP, Transfer Learning etc) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc)
  • Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc)
  • Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data
  • Solid understanding of summary, robust, and nonparametric statistics; hypothesis testing, probability distributions, sampling techniques, and stochastic processes

Be Customer Focused - constantly improving our customers' experience

  • I listen to my customers
  • I use available data to help make decisions

Be Human - acting with humanity and care

  • I do the right thing
  • I am respectful

Be Curious - thrive on learning, thinking beyond the obvious

  • I build and share new ideas
  • I try new things and share my learnings

Be Agile - working with trust, pace and agility

  • I have courage to be creative
  • Done is better than perfect, I aim for 80/20

Be Inclusive - acting inclusively in diverse teams to work together

  • I embrace allyship
  • I have self-awareness and a desire to learn

Be Accountable - championing the plan to deliver results and growth

  • I own my actions
  • I understand the Kingfisher plan and how it relates to my role

At Kingfisher, we value the perspectives that any new team members bring, and we want to hear from you. We encourage you to apply for one of our roles even if you do not feel you meet 100% of the requirements.


In return, we offer an inclusive environment, where what you can achieve is limited only by your imagination! We encourage new ideas, actively support experimentation, and strive to build an environment where everyone can be their best self. Find out more about Diversity & Inclusion at Kingfisher here!


We also offer a competitive benefits package and plenty of opportunities to stretch and grow your career.


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


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.