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Deep Learning Scientist at Plumerai (Amsterdam, Netherlands)

About Plumerai


We believe autonomy and embedded intelligence will be the most impactful technologies in the next decade and the lack of an efficient deep learning platform is the main thing holding this future back. Binarized Neural Networks (BNNs) can result in a theoretical 1000x performance improvement and we believe this is the way forward. Our team is based in London and Warsaw, with a new office opening in Amsterdam. We are backed by world-class investors with strong backgrounds in deep learning and with track records of founding multi-billion dollar chip and hardware companies.


Job Description:


We are looking for talented people to join our effort in enabling devices like robots and drones to use deep learning locally and in real time. We are researching new training algorithms for BNNs and are developing an open-source training library (Larq) to enable the academic community to do better research on BNNs. This work will enable the custom chip that we are designing to run BNN inference efficiently.


What You Will Be Doing:



  • You will work with a smart team that is researching, inventing and implementing both new and known algorithms for training deep learning models that will be radically more efficient.

  • You will contribute to the open source community and your work will result in academic publications.

  • You will tackle hard problems that have not been solved before and this requires both theoretical creativity and technical intuition.

  • You will develop theoretical guidance for BNNs and explore the behaviour of our models on a wide range of deep learning applications (e.g. object detection, depth estimation, SLAM, super-resolution).

  • You will work in close collaboration with our chip design team to discuss the implications of your algorithms on their work. This is how we can collectively push our hardware to its maximal performance.


Nice To Have:



  • PhD/Masters in Computer Science/Mathematics/Physics/Machine Learning.

  • Publications in top journals and conferences e.g. NeurIPS/ICML/ICLR/CVPR.

  • Academic or industrial experience in deep learning and computer vision.

  • Comfortable with frameworks such as TensorFlow, PyTorch or Caffe.

  • Ability to understand, write and implement cutting-edge research papers.

  • Ability to write high-quality code and familiar with code-reviewing, Python and Git.


What You Will Get:



  • Paid travel to top research and developer conferences.

  • Contributing to the open-source and research community is a fundamental part of your role.

  • Competitive base salary.

  • Company stock options.

  • Choose your own laptop.

  • 25 days of paid vacation time (plus bank holidays).

  • Flexible working hours.

  • Pension contribution.

  • Relocation assistance.