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- Tasks: Design and maintain infrastructure for ML models while collaborating with engineering teams.
- Company: Leading financial technology firm with a focus on innovation.
- Benefits: Competitive salary, stock options, and a generous benefits package.
- Why this job: Make a real impact in finance by scaling ML infrastructure and tools.
- Qualifications: Experience with AWS, Kubernetes, and strong problem-solving skills.
- Other info: Remote work options available within the UK or from the London office.
The predicted salary is between 43200 - 72000 £ per year.
A leading financial technology firm is seeking a Machine Learning Platform Engineer to design and maintain infrastructure and tools for ML models. You will work remotely within the UK or from the London office and collaborate with various engineering teams.
Ideal candidates will have experience with AWS, Kubernetes, and a strong inclination towards problem-solving and automation.
The role offers a competitive salary range along with stock options and a generous benefits package, making it an excellent opportunity for engineers looking to impact technology in finance.
ML Platform Engineer: Scale ML Infra & Cloud in London employer: Monzo Bank
Contact Detail:
Monzo Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Platform Engineer: Scale ML Infra & Cloud in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS and Kubernetes. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to ML infrastructure. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 about their job search!
We think you need these skills to ace ML Platform Engineer: Scale ML Infra & Cloud in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, Kubernetes, and any relevant problem-solving skills. We want to see how your background aligns with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about ML infrastructure and how you can contribute to our team. Keep it engaging and personal – we love getting to know the real you.
Showcase Your Projects: If you've worked on any cool projects related to machine learning or cloud infrastructure, make sure to mention them! We’re keen to see your hands-on experience and how you’ve tackled challenges in the past.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Monzo Bank
✨Know Your Tech Stack
Make sure you’re well-versed in AWS and Kubernetes, as these are crucial for the role. Brush up on your knowledge of how these technologies work together to support ML models, and be ready to discuss specific projects where you've used them.
✨Showcase Problem-Solving Skills
Prepare examples that highlight your problem-solving abilities, especially in relation to ML infrastructure. Think of challenges you've faced in previous roles and how you overcame them, as this will demonstrate your critical thinking and adaptability.
✨Understand the Financial Sector
Familiarise yourself with the financial technology landscape. Knowing how ML can impact finance will not only impress your interviewers but also show that you're genuinely interested in the role and its implications.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s ML initiatives and team dynamics. This shows your enthusiasm for the position and helps you gauge if the company culture aligns with your values and work style.