Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Enhance AI/ML products focusing on recommender systems and NLP solutions.
- Company: Global RegTech business with a focus on innovation.
- Benefits: Competitive salary, diverse team, and opportunities for innovation.
- Why this job: Work with cutting-edge technology and make a real impact in AI.
- Qualifications: Over two years of machine learning experience, strong Python and SQL skills.
- Other info: Dynamic environment with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A global RegTech business is seeking a Machine Learning Engineer to enhance their AI/ML-powered products, focusing on recommender systems and NLP solutions.
The ideal candidate will have over two years of experience in machine learning, particularly in NLP, and be capable of deploying scalable ML solutions in a cloud environment.
Strong Python and SQL skills are required, along with a systems thinking approach.
This role offers an opportunity to innovate and work with cutting-edge technology within a diverse team.
AI Engineer — NLP/LLM Systems & Cloud ML in London employer: CUBE
Contact Detail:
CUBE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer — NLP/LLM Systems & Cloud ML in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow AI 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 projects, especially those related to NLP and ML. This is your chance to demonstrate your expertise and passion for the field, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Practice common ML problems and be ready to discuss your thought process. We want to see how you approach challenges, so think out loud!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Engineer — NLP/LLM Systems & Cloud ML in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning, especially in NLP and cloud environments. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
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 your background makes you a perfect fit for our team. Let us know what excites you about working with cutting-edge technology.
Showcase Your Technical Skills: Since strong Python and SQL skills are a must, make sure to mention specific projects or experiences where you’ve used these languages. We love seeing practical examples of your work, so don’t hold back!
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’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at CUBE
✨Know Your NLP Inside Out
Make sure you brush up on your knowledge of Natural Language Processing (NLP) and Large Language Models (LLMs). Be prepared to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show your depth of understanding and practical experience.
✨Showcase Your Python and SQL Skills
Since strong Python and SQL skills are a must, be ready to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your thought process behind a previous project. Practising common algorithms and SQL queries can give you an edge.
✨Understand Cloud ML Deployment
Familiarise yourself with deploying machine learning models in a cloud environment. Be prepared to discuss the tools and platforms you’ve used, such as AWS, Google Cloud, or Azure. Highlight any experience you have with scaling solutions and managing resources effectively.
✨Emphasise Systems Thinking
This role requires a systems thinking approach, so be ready to talk about how you view problems holistically. Discuss how you integrate different components of a system and ensure they work together seamlessly. Providing examples from past experiences will help illustrate your point.
