FAQs
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.