Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and deploy robust AI models while optimising their performance.
- Company: Leading technology firm in London with a focus on innovation.
- Benefits: Flexible working hours, competitive salary, and professional development opportunities.
- Other info: Hybrid work model with a collaborative environment.
- Why this job: Join a dynamic team and work on cutting-edge AI technologies.
- Qualifications: 3–5 years of experience in ML, strong Python skills, and familiarity with modern frameworks.
The predicted salary is between 43200 - 72000 £ per year.
A leading technology firm in London seeks a Machine Learning Engineer to develop and deploy robust AI models. This role requires 3–5 years of experience, strong Python skills, and familiarity with modern ML frameworks.
You will be responsible for:
- Optimizing the performance of models
- Handling complex data engineering tasks
- Working closely with clients
The position offers competitive benefits, including flexible working hours and opportunities for professional development.
ML Engineer: Production AI & LLM/RAG (Hybrid, London) employer: Xantura Limited
Contact Detail:
Xantura Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer: Production AI & LLM/RAG (Hybrid, London)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow ML 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 involving AI models and Python. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML scenarios and be ready to discuss how you've optimised model performance in past roles.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace ML Engineer: Production AI & LLM/RAG (Hybrid, London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and ML frameworks. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
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. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any cool AI models or data engineering tasks, make sure to mention them in your application. We’re keen to see real-world examples of your work and how you’ve tackled challenges in the past.
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 Xantura Limited
✨Know Your ML Frameworks
Make sure you brush up on the modern ML frameworks mentioned in the job description. Be ready to discuss your experience with them and how you've used them in past projects. This shows you're not just familiar but also hands-on.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common algorithms and data structures in Python beforehand.
✨Understand the Client's Needs
As you'll be working closely with clients, it's crucial to understand their requirements. Research the company and think about how your role as an ML Engineer can directly impact their business. This will help you answer questions more effectively.
✨Prepare for Data Engineering Questions
Given that the role involves handling complex data engineering tasks, be prepared to discuss your experience with data pipelines and data manipulation. Think of specific examples where you've optimised data processes or solved data-related challenges.