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- Tasks: Design and build machine learning models to create intelligent solutions that change lives.
- Company: Join Specsavers, a leader in vision and hearing innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment focused on innovation and ethical practices.
- Why this job: Make a real-world impact with cutting-edge AI projects across various sectors.
- Qualifications: Strong Python skills, experience with ML techniques, and great communication abilities.
The predicted salary is between 50000 - 70000 £ per year.
We’re on a mission to change lives through better sight and hearing and we believe machine learning and AI are key to making that happen. That’s why we’re looking for a Machine Learning Engineer to join our growing AI & ML Engineering team. If you’re excited by the idea of building intelligent solutions that make a real-world impact, this could be the role for you.
This is your chance to work on some of the most exciting and forward-thinking projects in the business. You’ll be designing and building machine learning models, developing generative AI solutions, and helping us shape the future of AI agents across a global organisation. From supply chain and marketing to clinical and in-store experiences, your work will touch every part of the Specsavers journey.
You’ll collaborate with data engineers, MLOps specialists, and product owners to bring ideas to life turning complex challenges into smart, scalable solutions. We’re looking for someone who’s hands-on, curious, and ready to make a difference.
You’ll need strong experience in Python especially with the scikit learn ecosystem and MLFlow and be confident working with SQL to manipulate and cleanse large datasets. You’ll have a solid understanding of both supervised and unsupervised machine learning techniques, and you’ll know how to evaluate and deploy models in a cloud environment.
Experience with AI APIs, pretrained open-source models, and tools like Databricks or Azure Cognitive Services will be a big plus. If you’ve worked on end-to-end Gen AI solutions or have applied ML in retail or ecommerce settings, we definitely want to hear from you.
You’ll also need to be a great communicator able to explain complex technical ideas in a clear, compelling way to non-technical stakeholders. And just as importantly, you’ll bring a strong ethical mindset, a collaborative spirit, and a genuine enthusiasm for learning and innovation.
So, are you ready to help us unlock the power of AI? If you’re looking for a role where you can innovate, collaborate, and see the real-world impact of your work we’d love to hear from you. Join Specsavers and help us build a smarter, more connected future.
Machine Learning Engineer in Winchester employer: Specsavers
Contact Detail:
Specsavers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Winchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that demonstrate your experience with Python, SQL, and AI solutions. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to explain complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our mission to make a real-world impact.
We think you need these skills to ace Machine Learning Engineer in Winchester
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for machine learning and AI shine through. We want to see how excited you are about building intelligent solutions that make a real-world impact!
Highlight Relevant Experience: Make sure to showcase your experience with Python, scikit-learn, and SQL. Mention any projects where you've developed generative AI solutions or worked on end-to-end ML applications, especially in retail or ecommerce.
Communicate Clearly: Remember, we value great communication skills! Be sure to explain your technical expertise in a way that's easy to understand. This will show us that you can effectively collaborate with non-technical stakeholders.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Specsavers
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills, especially with the scikit-learn ecosystem and MLFlow. Be ready to discuss your experience with SQL and how you've manipulated large datasets in previous projects. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about real-world challenges you've faced in machine learning. Think of instances where you've designed and deployed models, particularly in cloud environments. Highlight any end-to-end Gen AI solutions you've worked on, especially in retail or e-commerce.
✨Communicate Clearly
Since you'll need to explain complex ideas to non-technical stakeholders, practice simplifying your explanations. Use analogies or relatable examples to make your points clear. This will show that you can bridge the gap between technical and non-technical teams.
✨Emphasise Your Collaborative Spirit
Be prepared to discuss how you've worked with cross-functional teams, like data engineers and product owners. Share examples of how collaboration led to successful project outcomes. This will demonstrate that you're not just a tech whiz but also a team player who values input from others.