You will
- work on machine learning research projects, in particular addressing the question of how machine learning methodologies can be further improved in order to achieve better performances in relevant applications; those applications are likely to be connected to either computer vision or natural language processing, however, also more general methodological questions might be of interest (e.g. meta learning, hyperparameter search, efficient training of neural networks)
- also work on transferring theoretical insights to practical use cases which are usually part of respective research projects, with the goal of setting new industry standards
- be able to publish your results in relevant journals or at machine learning conferences such as ICML, NeurIPS or ICLR
- foster our strong connections to academia, keep up to date with advances in machine learning research and actively take part in our company’s collaborative learning and development environment
- support the dida team in applying cutting-edge machine learning algorithms
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