Master Thesis Continous Learning and Data Acquisition in Machine Learning Operation (MLOps) (f/m/x)

Das ist der Job

Master Thesis Continous Learning and Data Acquisition in Machine Learning Operation (MLOps) (f/m/x) SOME IT WORKS.

Darum lohnt es sich

That’s why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table – and give you the opportunity to really show what you can do. SOME CHANGES WHAT'S POSSIBLE. SHARE YOUR PASSION. More than 90% of automotive innovations are based on electronics and software.

That's why creative freedom and lateral thinking are so important in the pursuit of truly novel solutions. We, the BMW Group, offer you an interesting and varied Master thesis in the area of Continous Learning and Data Acquisition in Machine Learning Operation (MLOps).

Machine Learning Operations (MLOps) aims to streamline the deployment, monitoring, and continuous development of machine learning models in production environments. One of the critical challenges in MLOps is ensuring that models remain up-to-date and perform well as new data becomes available.

Continuous learning addresses this challenge by focusing on the acquisition of data and the subsequent training enabling models to be adapted continuously over their lifetime.

This thesis aims to develop and optimize techniques for continuous learning and data acquisition within MLOps frameworks, enhancing the efficiency and effectiveness of machine learning operations. What awaits you? Research state-of-the-art continuous learning on Vision Transformers for semantic segmentation on benchmark dataset