Backend & Devops
Be integral to enhancing our backend and data architecture using technologies such as Python, Django, Apache Airflow, PostgreSQL, C#, Docker, and more. Your role can also include deploying solutions to the cloud or edge using Azure and Azure IoT, and refining our CI/CD Pipelines. You'll optimize data models, develop APIs, automate deployment processes, and ensure our systems' scalability and reliability.
Sarnen / Aachen
Working Student or Internship
What You’ll Do
- Alpamayo, a tech startup and CSEM spinoff, is focused on creating intelligent maintenance and quality solutions for industrial applications. Our goal is to make these solutions more accessible through the development of PREKIT, a framework for process monitoring and predictive analytics. Combining in-depth process expertise with the power of AI, we strive to meet the intricate needs of machine manufacturers.
PREKIT, our suite of software modules, is designed to encapsulate this approach. It empowers engineering teams to leverage their expert problem understanding to design powerful analytics solutions. The suite assists equipment manufacturers in providing valuable digital services to connected machines globally. Deployable as an end-to-end solution, PREKIT aids users right from initial pilot implementation to running a scalable, fully-managed service. Alternatively, it can seamlessly integrate with customers' existing digital ecosystems.
- As we grow, we're searching for driven student workers eager to join our technical team.
You will collaborate closely with our CTO in the following tasks and recieve excellent guidance in your journey to becoming a backend & devops engineer:
- Deploying solutions to the cloud or edge using Azure and Azure IoT.
- Refining our CI/CD pipelines.
- optimize data models, develop APIs, automate deployment processes, and ensure our systems' scalability and reliability.
Who You are
- - Educational Background: Pursuing a degree Computer Science, or related field.
- AI & Machine Learning: Familiarity with AI methodologies and the development of machine learning algorithms.
- Adaptability: Comfortable in fast-paced environments with the aptitude to learn quickly and pivot tasks when required.
- Initiative: Willingness to take ownership of tasks, from conception to deployment, and drive projects forward.