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- Tasks: Establish and manage the reliability of an AI cloud platform.
- Company: Wayve, a forward-thinking tech company based in London.
- Benefits: Hybrid working model, diverse environment, and opportunities for growth.
- Other info: Be part of a diverse and inclusive workplace.
- Why this job: Join a pioneering team and shape the future of AI technology.
- Qualifications: Experience with large-scale cloud systems and Kubernetes required.
The predicted salary is between 80000 - 100000 £ per year.
Wayve, based in London, is seeking a Staff Cloud Site Reliability Engineer to establish and manage the reliability of their AI cloud platform. This role involves building the operational standards for their Model Development Platform and GPU Compute infrastructure, requiring extensive experience in large-scale cloud systems and Kubernetes. The position follows a hybrid working model with two days a week in the office, aiming to create a diverse and inclusive work environment.
Founding Cloud SRE: AI/ML Platform & GPU Compute in London employer: Wayve
Contact Detail:
Wayve Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Cloud SRE: AI/ML Platform & GPU Compute in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Wayve. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got experience with Kubernetes or large-scale cloud systems, make sure to highlight that in conversations. We want to see how you can bring value to the team!
✨Tip Number 3
Prepare for the interview by diving deep into Wayve's projects and values. Understanding their AI cloud platform will help you connect your expertise to their needs, making you a standout candidate.
✨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 take that extra step to engage with us directly.
We think you need these skills to ace Founding Cloud SRE: AI/ML Platform & GPU Compute in London
Some tips for your application 🫡
Show Your Passion for AI/ML: When writing your application, let us see your enthusiasm for AI and machine learning. Share any relevant projects or experiences that highlight your interest in these areas, as it’ll help us understand why you’re a great fit for our team.
Highlight Your Cloud Experience: Make sure to emphasise your experience with large-scale cloud systems and Kubernetes. We want to know about the challenges you've faced and how you've tackled them, so don’t hold back on the details!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention how your skills align with the responsibilities of establishing operational standards for our Model Development Platform and GPU Compute infrastructure.
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 Wayve
✨Know Your Cloud Inside Out
Make sure you brush up on your knowledge of large-scale cloud systems and Kubernetes. Be ready to discuss your previous experiences with these technologies, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've improved reliability in past projects. Think about metrics you can present that demonstrate your impact, as this will show Wayve that you can bring value to their AI cloud platform.
✨Understand the Company Culture
Wayve values diversity and inclusion, so do a bit of research on their work environment. Be prepared to discuss how you can contribute to this culture and why it matters to you. This will help you connect with the interviewers on a personal level.
✨Ask Insightful Questions
Prepare thoughtful questions about the role and the team dynamics. Inquire about their operational standards for the Model Development Platform and GPU Compute infrastructure. This shows your genuine interest in the position and helps you assess if it's the right fit for you.