Working Student GenAI Training and Model Workflows

Life is always about becoming... In life it is about going on a journey to become the best version of our future self. As we discover new things, we face challenges, master them and grow beyond us.

Apply to Mercedes-Benz and find the area where you can develop your talents individually. You will be supported by visionary colleagues who share your pioneering spirit. Joining us means becoming part of a global team whose goal is to build the most desirable cars in the world. Together for excellence.

Number: MER0003O3R Generative AI meets Design – thanks to the latest GenAI solutions (Image Generation, Video Generation, Research on 3D generation,.) merge creative areas and artificial intelligence at a rapid pace. To the potential of this technology for our internal design processes You will continue to expand various commercial and open source solutions and train your own AI models. Whether diffusion models or related architectures: You expect 12 months of hands-on AI training and coding. These challenges come to you, among others You talk to design colleagues to understand their design requirements and to derive appropriate training parameters if necessary You prepare training data and check or evaluate appropriate diffusion checkpoint models You carry out training and fine-tuning systematically and scientifically to determine ideal training parameters Processing of 2D and 3D data Create workflows from your models to use them by designers Fine tuning, workflows etc. are written by you (for example in markdowns) The work student activity can start from August 2025.

studies in a scientific field (or computer science; Data Science o.A.) with focus or experience in deep learning Coding experiences with Python and one of the usual machine learning libraries such as jax, pytorch, tensorflow or the high-level API keras Ideally first experiences in the field of Generative AI - for example Variational Autoencoder, Generative Adversarial Networks or Diffusion Models Experience with Vision Models and/or LLMs Experience in Blender (Advantage) First experiences of Lora trainings as part of Stable Diffusion, Flux are advantageous Coding best practices and awareness of sustainable code and documentation Secure knowledge of German and English in word and writing Safe handling of MS Office Commitment and team skills Analytical thinking and strategic working

Additional information: Of course, without formalities, we are not. Please apply exclusively online and add a CV to your application, current enrollment certificate with semester indication, current grade, relevant certificates, if applicable. Compulsory internship certificate and proof of the rule period (maximum size of the annexes 5 MB) and in the online form mark your application documents as ''relevant for this application'. Further information on the setting criteria can be found here. Members of countries outside the European Economic Area may send their residence/work permit. We are particularly pleased to receive online applications of disabled people and disabled people. If you have any questions, you can also contact sbv-sindelfingen@mercedes-benz.com to the site's severely disabled representative, who will be happy to support you in the further application process after your application. Please understand that we no longer accept paper applications and there is no claim to return. Questions about the application process will be answered by HR Services by e-mail to myhrservice@mercedes-benz.com or by phone: 0711/17-99000 (Monday to Friday between 10-12 am and 13-15 pm).

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