Machine Learning Engineer in London

Machine Learning Engineer in London

London Full-Time 50000 - 70000 £ / year (est.) Home office (partial)

At a Glance

  • Tasks: Develop and deploy machine learning models to enhance customer experiences.
  • Company: Join Kingfisher, a leading retail group with a passion for better homes.
  • Benefits: Flexible hybrid working, competitive salary, and opportunities for career growth.
  • Other info: Inclusive culture that values creativity and collaboration.
  • Why this job: Make a real impact on millions of customers while working with cutting-edge AI technology.
  • Qualifications: Strong Python skills and experience with machine learning techniques required.

The predicted salary is between 50000 - 70000 £ per year.

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.

Machine Learning Engineer in London employer: 慨正橡扯

At Kingfisher, we pride ourselves on being an exceptional employer, fostering a culture of inclusivity and innovation where every team member can thrive. As a Machine Learning Engineer, you will have the opportunity to work within a dynamic engineering team, contributing to impactful AI solutions that enhance the customer experience across our renowned retail brands. With a flexible hybrid working model, competitive benefits, and a commitment to personal growth, Kingfisher is dedicated to empowering you to reach your full potential while making a meaningful difference in the world of home improvement.

Contact Details:

慨正橡扯 Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer in London

Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups or webinars, and connect with current employees at Kingfisher. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

Tip Number 2

Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it’s a GitHub repo or a personal website, having tangible examples of your work can really make you stand out during interviews.

Tip Number 3

Prepare for technical interviews by brushing up on your coding skills and algorithms. Practice common machine learning problems and be ready to discuss your thought process. We want to see how you tackle challenges!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Kingfisher team. Let’s make it happen!

We think you need these skills to ace Machine Learning Engineer in London

Machine Learning
Artificial Intelligence
Python
Pandas
scikit-learn
Jupyter
SQL

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight relevant experience, especially with Python and machine learning techniques. We want to see how your skills align with what we're looking for!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how you can contribute to our mission of Better Homes. Better Lives. For Everyone. Keep it engaging and personal.

Showcase Your Projects:If you've worked on any cool machine learning projects, make sure to mention them! Whether it's a personal project or something from a previous job, we love seeing practical applications of your skills.

Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you're keen to join our team!

How to prepare for a job interview at 慨正橡扯

Know Your Machine Learning Stuff

Make sure you brush up on your machine learning fundamentals. Be ready to discuss classical techniques and modern approaches like deep learning and natural language processing. They’ll likely want to know how you’ve applied these in real-world scenarios, so have some examples up your sleeve.

Show Off Your Coding Skills

Since strong Python skills are a must, be prepared to demonstrate your coding abilities. You might be asked to write production-quality code or solve a problem on the spot. Practise using libraries like Pandas and scikit-learn, and make sure you can explain your thought process clearly.

Understand the Deployment Process

Familiarise yourself with the tools and practices for deploying models, such as Git and CI workflows. Be ready to discuss how you’ve monitored and optimised model performance in a production environment. This shows you’re not just about building models but also about making them work effectively.

Emphasise Collaboration

Kingfisher values teamwork, so highlight your ability to work collaboratively. Share examples of how you’ve communicated with colleagues to understand requirements and priorities. Show that you can contribute to a positive team culture and support others in achieving shared goals.