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- Tasks: Learn and apply machine learning skills while collaborating with experts in the field.
- Company: Leading tech company in Scotland with a focus on innovation.
- Benefits: Competitive salary, health insurance, life insurance, and pension plan.
- Why this job: Kickstart your career in machine learning and gain hands-on experience.
- Qualifications: Coding skills, basic ML knowledge, and a passion for learning.
- Other info: Join a dynamic team and grow your career in a thriving industry.
The predicted salary is between 22000 - 25000 £ per year.
A leading technology company in Scotland is offering a Level 6 Machine Learning Apprenticeship. This role focuses on developing skills in the entire machine learning lifecycle while collaborating with data scientists and software engineers.
The competitive salary ranges from £22,000 to £25,000 and includes a generous benefits package, such as health and life insurance and a pension plan.
Candidates should possess coding skills, a basic understanding of ML, and a strong desire to learn.
Machine Learning Apprentice: Build, Deploy & Learn employer: Domino Sweden
Contact Detail:
Domino Sweden Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Apprentice: Build, Deploy & Learn
✨Tip Number 1
Network like a pro! Reach out to current or former apprentices in the field. They can give you insider tips and maybe even refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing any projects you've worked on, especially those related to machine learning. This will help you stand out during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on coding challenges and ML concepts. Practise explaining your thought process clearly, as communication is key in tech roles.
✨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, we love seeing candidates who are proactive!
We think you need these skills to ace Machine Learning Apprentice: Build, Deploy & Learn
Some tips for your application 🫡
Show Off Your Coding Skills: Make sure to highlight your coding skills in your application. We want to see what you can do, so include any relevant projects or experiences that showcase your abilities!
Demonstrate Your Passion for ML: Let us know why you're excited about machine learning! Share any personal projects, courses, or experiences that sparked your interest in this field. We love seeing candidates who are eager to learn and grow.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to the role. Mention specific aspects of the job description that resonate with you and how you can contribute to our team.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at Domino Sweden
✨Know Your ML Basics
Make sure you brush up on your machine learning fundamentals. Understand key concepts like supervised vs unsupervised learning, common algorithms, and the machine learning lifecycle. This will help you answer technical questions confidently.
✨Show Off Your Coding Skills
Be prepared to discuss your coding experience. Bring examples of projects you've worked on, especially those related to machine learning. If you can, demonstrate your problem-solving skills through coding challenges or by explaining your thought process.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the apprenticeship, the team you'll be working with, and the technologies they use. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
✨Express Your Eagerness to Learn
Since this is an apprenticeship, highlight your passion for learning and growth. Share examples of how you've pursued knowledge in the past, whether through online courses, personal projects, or collaboration with others. Companies love candidates who are eager to develop their skills!
