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- Tasks: Support and maintain advanced AI systems with large Kubernetes clusters.
- Company: Leading AI research organisation in the UK with a focus on innovation.
- Benefits: Competitive salary and hybrid work policy for flexibility.
- Why this job: Join a dynamic team and contribute to cutting-edge AI technology.
- Qualifications: Experience in distributed systems and strong programming skills.
- Other info: Opportunity to work in a high-performing, scalable infrastructure environment.
The predicted salary is between 43200 - 72000 £ per year.
A leading AI research organization in the United Kingdom seeks talented Infrastructure Engineers to join their Core Infrastructure team. In this role, you will support the development, scaling, and maintenance of advanced AI systems, building large Kubernetes clusters and ensuring infrastructure is reliable, scalable, and high-performing.
Ideal candidates will have experience in distributed systems and strong programming skills. This position offers competitive salaries and a hybrid work policy.
Senior Infrastructure Engineer: Kubernetes for AI Compute in London employer: Anthropic
Contact Detail:
Anthropic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Infrastructure Engineer: Kubernetes for AI Compute in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the organisation on LinkedIn. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects related to Kubernetes and AI systems. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for Infrastructure Engineers, especially those focusing on distributed systems and Kubernetes. Mock interviews can really help us nail it.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive roles listed there that you won’t find anywhere else.
We think you need these skills to ace Senior Infrastructure Engineer: Kubernetes for AI Compute in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Kubernetes and distributed systems. 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 infrastructure. We love seeing candidates who are genuinely excited about what we do at StudySmarter.
Showcase Your Programming Skills: Since strong programming skills are key for this role, include examples of your coding experience. Whether it's a project or a specific technology you've worked with, let us know how you’ve used your skills in real-world scenarios.
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!
How to prepare for a job interview at Anthropic
✨Know Your Kubernetes Inside Out
Make sure you brush up on your Kubernetes knowledge before the interview. Be ready to discuss your experience with building and managing large clusters, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Distributed Systems Experience
Prepare examples of your work with distributed systems. Highlight specific projects where you contributed to scaling or maintaining infrastructure, and be ready to explain the impact of your contributions on system performance.
✨Demonstrate Strong Programming Skills
Since strong programming skills are a must, be prepared to talk about the languages you’re proficient in. Bring examples of code you've written or projects you've worked on that showcase your ability to solve complex problems.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the tools they use, or their approach to scaling AI systems. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
