Background:
With the growing complexity of software engineering and data management in modern production environments, there is a pressing need for reliable and efficient software solutions. An MLOps platform has been developed to streamline the deployment and management of machine learning models in production. Ensuring the stability and robustness of this platform is crucial for its success.
Objective:
The primary goal is to develop and implement unit and integration tests for the MLOps platform, ensuring that all components work as intended and meet the required standards. This will help maintain the platform’s reliability, facilitate continuous integration, and support the seamless deployment of machine learning models. Furthermore, the tests will be integrated into a CI pipeline.
Tasks:
- Gain a deep understanding of the MLOps platform’s architecture and key functionalities.
- Study the existing codebase (Python) and identify areas requiring unit and integration tests.
- Design and implement unit tests using industry-standard tools and frameworks.
- Evaluate the effectiveness of the tests and make necessary improvements.
- Document the testing procedures and results.
Requirements:
- Interest in software testing and quality assurance.
- Prior practical experience with Python and unit testing frameworks (e.g., pytest).
- Strong analytical and problem-solving skills.
- Motivation, curiosity, and a structured approach to work.
- Good command of the German or English language, both written and spoken.
Applications with a resume and current transcript of records should be sent via email to tim.raffin@faps.fau.de and benedikt.scheffler@faps.fau.de.
Contact:
Tim Raffin, M.Sc.