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- Tasks: Develop tools to enhance AI software development and manage Cloud Infrastructure.
- Company: Cutting-edge AI technology company in Bristol with a dynamic team.
- Benefits: Competitive salary and numerous benefits for a great work environment.
- Other info: Exciting opportunities for growth in a fast-paced industry.
- Why this job: Join a team shaping the future of AI with innovative technologies.
- Qualifications: Knowledge of Python, Linux, and cloud services required.
The predicted salary is between 50000 - 60000 £ per year.
A cutting-edge AI technology company is looking for a skilled Software Infrastructure Engineer to join their dynamic team in Bristol. The role involves developing essential tools for enhancing the AI software development lifecycle, managing Cloud Infrastructure with Terraform and deploying services using Kubernetes and Docker.
Candidates should have knowledge of programming languages like Python, experience in Linux environments, and familiarity with cloud services.
The company offers a competitive salary and numerous benefits to ensure a great work environment.
MLOps & Infrastructure Engineer | Kubernetes & Terraform employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps & Infrastructure Engineer | Kubernetes & Terraform
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, or join online forums. 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 with Kubernetes, Terraform, and any AI tools you've worked on. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge, especially around cloud services and programming languages like Python. Practice common interview questions and be ready to demonstrate your problem-solving skills.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find the right role that matches your skills and interests. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace MLOps & Infrastructure Engineer | Kubernetes & Terraform
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Kubernetes, Terraform, and any programming languages like Python. 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! Tell us why you’re excited about the MLOps & Infrastructure Engineer position and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Cloud Knowledge: Since we’re all about cloud infrastructure, make sure to mention any experience you have with cloud services. Whether it's AWS, Azure, or Google Cloud, let us know how you've used these tools in your previous roles.
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 graphcore
✨Know Your Tech Stack
Make sure you brush up on your knowledge of Kubernetes, Terraform, and Docker. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Programming Skills
Since Python is a key language for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain a piece of code, so practice common algorithms and data structures beforehand.
✨Familiarise Yourself with Cloud Services
Understand the cloud services relevant to the role. Be prepared to discuss your experience with different cloud platforms and how you've managed infrastructure in the cloud. This will show that you're not just familiar with the tools but can also apply them effectively.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about their AI development lifecycle, team dynamics, and future projects. This shows your genuine interest in the role and helps you assess if it's the right fit for you.