Machine Learning Engineer

kingfisher -
London

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Job details

Full-time
14 days ago

Qualifications

Data structures
Git
SQL
Pandas
Machine learning
Deep learning
Natural language processing
Data pipeline
Python

Full job description

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. 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.

What's the job?

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

What you'll bring

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 involving in-person collaboration.

We value the perspectives new team members bring and encourage you to apply - even if you don’t meet 100% of the requirements.

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. 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. Scroll down below to find out more about our benefits.

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.

#LI-TB1 #LI-HYBRID

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Overview

What's the job?

What you'll bring

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