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- Tasks: Design, create, and maintain scalable cloud infrastructure for ML research.
- Company: Join a team revolutionizing therapeutics through cutting-edge technology.
- Benefits: Work with innovative tech and make a real impact in science.
- Why this job: Perfect for engineers passionate about science and machine learning.
- Qualifications: Experience in cloud infrastructure and backend technologies required.
- Other info: No ML experience needed, but familiarity with production ML deployment is a plus.
The predicted salary is between 43200 - 72000 £ per year.
This role is ideally suited to an experienced software engineer, who loves building scalable cloud infrastructure and applies software engineering principles to infrastructure code. As a member of our engineering team, you will play a key role in designing, creating, and maintaining infrastructure that allows our ML research scientists to run training and inference on a massive scale, and help deliver model results to molecular scientists.
If you’re a software engineer who is interested in science and ML, you’ll be at home here. No machine learning experience is required for this role, although experience with production ML model deployment would be beneficial. Using your talent for writing and maintaining reliable systems, you will play a key role in revolutionising the creation of cutting-edge therapeutics.
Who are you
- A skilled engineer who is excited about developing and deploying infrastructure that will have an immediate impact on the engineering team.
- Solid understanding and working knowledge of backend and cloud technologies.
- A passionate developer who loves the challenge of writing testable code.
Useful skills
- Expert knowledge of cloud infrastructure (AWS preferred), including multi-account setups and best practices.
- Cloud engineering – using infrastructure as code (IaC) tooling (Terraform, Pulumi, CloudFormation).
- Containerised application/tool development using Docker or Kubernetes.
- Solid development skills (Python/Typescript preferred), with an ability to structure code for testability.
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Senior Platform Engineer employer: Karkidi
Contact Detail:
Karkidi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Platform Engineer
✨Tip Number 1
Familiarize yourself with the latest trends in cloud infrastructure, especially AWS. Understanding multi-account setups and best practices will give you a significant edge during discussions with our engineering team.
✨Tip Number 2
Get hands-on experience with Infrastructure as Code (IaC) tools like Terraform or Pulumi. Being able to demonstrate your ability to manage infrastructure through code will showcase your skills effectively.
✨Tip Number 3
Brush up on your containerization skills, particularly with Docker and Kubernetes. Having practical knowledge in deploying applications in containers can set you apart from other candidates.
✨Tip Number 4
Since we value testable code, consider working on personal projects that emphasize writing clean, testable code in Python or Typescript. This will not only enhance your skills but also provide concrete examples to discuss during the interview.
We think you need these skills to ace Senior Platform Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with cloud infrastructure, backend technologies, and any relevant programming languages like Python or Typescript. Emphasize your skills in writing testable code and any experience with IaC tools such as Terraform or CloudFormation.
Craft a Compelling Cover Letter: In your cover letter, express your passion for developing scalable cloud infrastructure and how it relates to the role. Mention your interest in science and machine learning, even if you don't have direct experience, to show your enthusiasm for the field.
Showcase Relevant Projects: If you have worked on projects involving containerized applications or cloud engineering, be sure to include these in your application. Describe your role and the impact of your contributions to demonstrate your hands-on experience.
Highlight Problem-Solving Skills: Use specific examples in your application to illustrate how you've tackled challenges in previous roles. This could include optimizing cloud infrastructure or improving system reliability, showcasing your ability to develop solutions that have a real impact.
How to prepare for a job interview at Karkidi
✨Show Your Passion for Cloud Infrastructure
Make sure to express your enthusiasm for building scalable cloud infrastructure. Share specific examples of projects where you applied software engineering principles to infrastructure code, highlighting your experience with AWS and IaC tools like Terraform or Pulumi.
✨Demonstrate Your Coding Skills
Prepare to discuss your development skills in Python or Typescript. Be ready to explain how you structure your code for testability and reliability, as this is crucial for the role. Consider bringing a code sample that showcases your best practices.
✨Understand the Role of ML in Infrastructure
Even though machine learning experience isn't required, showing an understanding of how infrastructure supports ML research can set you apart. Discuss any relevant experiences or knowledge you have about deploying production ML models and how it relates to the infrastructure you build.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's engineering team and their current projects. Inquire about the challenges they face in building infrastructure for ML research, as this shows your genuine interest in contributing to their goals.
