Company Description
At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.
The Robert Bosch GmbH is looking forward to your application!
Job Description
Foundation Models revolutionize the development of custom DL applications as they can be adapted to a wide range of downstream tasks using only little amounts of data. Due to their size and computational requirements, they are often too computationally expensive to run on resource-constrained devices such as smart sensors.
- The goal of this internship is to combine methods from neural architecture search and quantization to compress FMs for efficient deployment and usage on various target hardware platforms.
- As part of the automated machine learning team, you will work on novel approaches to compress and adapt Foundation Models to resource-constrained devices.
- Your tasks involve combining techniques from model compression (e.g., quantization, pruning, knowledge distillation) with methods from automated machine learning (e.g., hyperparameter optimization, neural architecture search) as well as developing new methods that can leverage Foundation Models for deployment of custom DL applications.
- You are responsible for the implementation and evaluation of the developed methods on academic benchmark datasets as well as internal datasets (e.g., for autonomous driving).
- You take an active role in Bosch Center for AI (BCAI), the main hub for AI research and technology development across Bosch, where you can discuss and develop new ideas with our leading experts on artificial intelligence.
- You will present and publish your results internally at the Bosch Center for AI but, if possible, also in top-tier scientific conferences and journals.
Qualifications
- Education: Master studies in the field of Computer Science, Computer Vision, Deep Learning or comparable with excellent grades
- Experience and Knowledge: Background in deep learning and computer vision, experience with deep learning frameworks (TensorFlow, PyTorch, etc.), good programming skills, in particular Python, knowledge and experience in model compression, automated machine learning as well as foundation models are a plus, experience with publication of peer-reviewed research papers is beneficial
- Enthusiasm: motivation to work in an interdisciplinary and international team
- Languages: very good English skills
Additional Information
Start: according to prior agreement
Duration: 6 months
Requirement for this internship is the enrollment at university. Please attach a motivation letter, your CV, transcript of records, enrollment certificate, examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.
Need further information about the job?
Benedikt Staffler (Business Department)
+49 173 390 1364
Martin Rapp (Business Department)
+49 162 726 7668
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