Working student Machine Learning Engineering (m/f/x)

Your tasks?

As a working student (m/f/x) in machine learning engineering, you support the team in further developing large language models (LLMs) into multimodal models for audio and vision applications.

You research, create, and prepare high-quality multimodal data sets for the training and further development of the models.

You also support the creation and management of data, training and evaluation pipelines in the cloud.

In fine tuning of existing base models, such as Qwen, you appear on multimodal and capability-specific data.

In doing so, you deal with modern approaches such as RAG, tool calling and agent behavior and support their use and further development.

In addition, you work together with experienced developers from different disciplines in an agile product development team and actively contribute your ideas.

Your profile?

You study computer science, data science, artificial intelligence, machine learning or a comparable course of study.

You will bring experience in software development with Python as well as in training deep learning and machine learning models.

You understand how large language models work and are trained, and you'll be interested in their further development and practical application.

Ideally, you will already have some practical experience of creating data sets, such as data preprocessing, filtering or augmentation, or programming LLM-supported applications.

Experience with cloud development and platforms such as Databricks or Azure is an advantage.

Good written and spoken German and English round off your profile.