Working Student for Computer Vision and Generative AI starting June 2024

Mercedes - Benz AG

Job Description
Life is always about becoming… Becoming means going on a journey to be the best version of our future selves. While we discover new things, we will face challenges, master them and grow beyond our individual limits.

Apply for a job at Mercedes-Benz and find your individual role and workspace to unleash your talents to the fullest. Empowered by visionary colleagues who share the same pioneering spirit. Joining us means becoming part of a global team that aims to build the most desirable cars in the world. Together for excellence.

Job-ID: MER00035KI

Are you passionate about robots taking over the world? Then look no further! We are constantly looking for highly motivated students to join our autonomous car research team in Stuttgart, Germany in the following area:

Current sensors such as stereo cameras or lidar often malfunction or even fail in adverse weather where the accident risk is very high. Within the publicly funded projects AI-SEE (ai-see.eu) and nxtAIM (nxtaim.de), we experiment with novel neural network architectures and sensor fusion networks to enhance disturbed sensor streams and to make object detection robust in adverse weather. Moreover, we apply our algorithms onto latest innovative sensor technologies developed in the projects to enable autonomous cars to drive in every situation. You can expect plenty of GPU resources, international colleagues and the occasional cake (you need to bring one too).


Minimum Skills Required:

  • Pursuing a Master's degree in a highly quantitative field such as Computer Science, Physics, Mathematics, Electrical Engineering or adjacent fields
  • Looking for a Working Student or a Master Thesis
  • Fluency in English and/or German
  • Strong programming skills in an object oriented programming language such as Python/ C++
  • Familiarity with Linux
  • Ability to think ahead/Independence

Nice to haves but not required:

  • Familiarity with deep learning frameworks such as Tensorflow or PyTorch
  • Familiarity with Computer Vision, Foundation Models, Generative AI
  • Familiar with Convolutional Neural Networks/Vision Transformers/Diffusion Networks
  • Experience in deep-learning based Object Detection/Depth Estimation/Semantic Segmentation

Additional Information:

  • The position is at our research lab in Böblingen
  • We prefer candidates available for 6-12 months
  • For more information don't hesitate to write a mail

Additional information:

It doesn't work completely without formalities. When sending your online application, please attach your CV, certificate of enrollment, current performance record, relevant certificates, if applicable proof of mandatory internship and the standard period of study (max. 5 MB) and mark your application documents as "relevant for this application" in the online form.

Please find the criteria of employment "here".

Citizens of countries outside the European Trade Union please send, if applicable, your residence / work permit.

We particularly welcome online applications from candidates with disabilities or similar impairments in direct response to this job advertisement. If you have any questions, you can contact the local disability officer once you have submitted your application form, who will gladly assist you in the onward application process: [email protected]

Please understand that we no longer accept paper applications and that there is no right to get your documents returned.

If you have any questions regarding the application process, please contact HR Services by e-mail at [email protected] or by phone: 0711/17-99000 (Monday to Friday between 10 a.m. to 12 a.m. and 1 p.m. to 3 p.m.).


  • Meal-Discounts
  • Mobile Phone possible
  • Discounts for employees possible
  • Annual profit share possible
  • Events for employees
  • Coaching
  • Flexitime possible
  • Hybrid Work possible
  • Health Benefits
  • Company Retirement
  • Mobility offers
  • Good public transport
  • Canteen, Café
  • Inhouse Doctor
  • Barrier-free workplace
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