The Role: 

As a Cloud Engineer for The U Group & Co, you will be an integral part of our Platform team, working to streamline our deployment processes and manage our infrastructure efficiently. You will collaborate closely with machine learning engineers to build and maintain a robust, scalable, and secure infrastructure to support the rapid development and deployment of our ML models. You will also interact with Data Delivery Engineers to support their data pipelines.

Reporting to: You will be reporting to the Head of Engineering

Skills and Experience:

REQUIRED

• Bachelor's degree in Computer Science, or a related field

• At least 3 years of experience in a cloud engineering role, with strong expertise in cloud services and infrastructure.

• Proficient in cloud services (AWS, GCP, Azure), with at least 3 years of hands-on experience in cloud architecture and deployments.

• Experience in designing and implementing scalable, reliable, and cost-effective cloud solutions.

• Knowledge of Amazon AWS (Certified AWS Cloud practitioner or higher) and infrastructure as code tools (e.g., CDK, Pulumi, CloudFormation).

• Proficient in scripting languages like Python or Bash.

• Familiarity with version control systems such as Git

• Strong experience with CI/CD tools (e.g., GitHub actions, Jenkins).

• Experience with containerisation and orchestration technologies (e.g., Docker, Kubernetes).

• Solid understanding of network protocols and security best practices.

• Strong problem-solving skills and the ability to work under tight deadlines.

PREFERRED

• Experience in managing and automating machine learning pipelines.

• Familiarity with data version control systems (e.g., DVC).

• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) is a plus.

What you will be doing:

• Design and implement robust cloud infrastructure to support machine learning and data delivery operations.

• Manage and optimize cloud resources for scalability and cost-effectiveness.

• Work with ML engineers to containerize and scale ML models across various environments.

• Work with data and software engineers to improve the scalability and reliability of our services

• Design, implement, and manage CI/CD pipelines including pipelines tailored for machine learning model training and deployment.

• Automate infrastructure provisioning and scaling to handle increased loads during holiday peaks, model training and inference.

• Ensure security best practices are followed throughout the infrastructure and deployment pipelines.

• Monitor system performance, resolving issues and outages (sometimes out of hours), and optimizing for scalability.

• Document infrastructure changes and pipeline processes.

• Stay up-to-date with new technologies and advocate for their adoption where appropriate.