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Lead Machine Learning Engineer

  • Job
    Senior & Expert Level
  • Data
  • London

AI generated summary

  • You must have strong expertise in AI product delivery, cloud-based ML services, classical and modern algorithms, SQL/Python, software development, Kubernetes, team management, and excellent communication skills.
  • You will lead data science projects, develop a team of ML Engineers, collaborate across teams, champion data science, and support a data-driven culture at Kingfisher.


  • Proven experience delivering high-quality AI-based products and productionisation of Machine Learning based products
  • Proven experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP)
  • Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.)
  • Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib)
  • Strong software development skills (Python is the preferred language)
  • Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow
  • Strong management and leadership skills – previous experience managing a team
  • Strong influencing, communication and stakeholder management skills
  • Be Customer Focused – constantly improving our customers’ experience
  • We listen to our customers and colleagues
  • We innovate products and experiences to stay ahead
  • Be Human – leading with purpose, humanity and care
  • We do the right thing
  • We invest in our people and build great teams
  • Be Curious – thrive on learning, thinking beyond the obvious
  • We focus externally, globally and build the long term
  • We experiment and share our learnings
  • Be Agile – building trust and empowering people to work with agility
  • We act with pace, not perfection, role modelling 80/20
  • We take risks, fail fast and adapt quickly
  • Be Inclusive – inspiring diverse teams to achieve together
  • We celebrate difference as a strength
  • We collaborate, breaking down silos
  • Be Accountable – owning the plan, delivering results and growth
  • We focus on performance outcomes
  • We prioritise and simplify for others


  • Lead the implementation of data science projects and data science approaches to support commercial goals
  • Develop a highly proficient team of Machine Learning Engineers, establishing collaborative ways of working
  • Collaborate with tech, product and data teams to develop the data platforms that allow us to apply data science and embed the use of data science directly in our products and processes
  • Support diverse teams in translating between business and data in the design of project work, and in the synthesis and communication of recommendations and results
  • Be a champion and role model for the application of data science across the Kingfisher group
  • Support the data leadership team in developing a “data culture” and demonstrating the value of data in our decision making
  • Lead our efforts to develop the data science (and broader customer analytics) “brand” at Kingfisher for both internal and external audiences


What qualifications and experience are required for the Lead Machine Learning Engineer role at Kingfisher?

To be successful in the role of Lead Machine Learning Engineer at Kingfisher, you should have proven experience delivering high-quality AI-based products and productionisation of Machine Learning based products. You should also have experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP), a strong understanding of classical Machine Learning algorithms and modern Deep Learning algorithms, as well as proficiency in SQL and Python's ecosystem for data analysis. Additionally, strong software development skills in Python, experience deploying ML/AI services using Kubernetes & KubeFlow, and strong management and leadership skills are required for this role.

What benefits does Kingfisher offer to its employees?

Kingfisher offers a competitive benefits package to its employees, including Private Health Care with family level cover options, participation in the Kingfisher Pension Scheme, 25 days' holiday per annum, a 20% staff discount at B&Q and Screwfix, participation in the Kingfisher Share Incentive Plan (SIP), Life Assurance, a competitive bonus scheme, and the opportunity to participate in the Kingfisher Share Save scheme.

What is the application process like for the Lead Machine Learning Engineer role at Kingfisher?

The application process for the Lead Machine Learning Engineer role at Kingfisher involves several steps. Firstly, applicants are required to submit their application through the Kingfisher Careers website. If selected, candidates will have a telephone interview or one-to-one conversation with a recruiter, followed by a face-to-face or virtual interview. Feedback will be provided after each stage of the process, and successful candidates will receive details of the job offer.

Retail & Consumer Goods

Mission & Purpose

Kingfisher plc is an international home improvement company with approximately 1,900 stores, and operations in eight countries across Europe. We operate under retail banners including B&Q, Castorama, Brico Dépôt, Screwfix, TradePoint and Koçtaş, supported by a team of over 82,000 colleagues. We offer home improvement products and services to consumers and trade professionals who shop in our stores and via our e-commerce channels. At Kingfisher, we believe a better world starts with better homes. We help make better homes accessible for everyone. As a Group, we use our core strengths and commercial assets, and we power our retail banners to address the significant growth opportunities that exist within the home improvement market #PoweredByKingfisher