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Deep Learning Research Engineer

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Job description

We're hiring software engineers and deep learning researchers to join our research and development team.


Our R&D team focuses on applied deep learning algorithms and software in computer vision, sound and natural language processing. Previous and ongoing projects include and are not limited to prediction and scene comprehension for assisted driving technologies, face recognition, image and sound synthesis, natural language understanding.


We value potential as much as experience and above all an enthusiastic attitude towards this research field.

Job responsibilities

As a research engineer at Arnia, you'll be tasked with developing and implementing machine learning algorithms and applying them to practical on-going projects.


You will be part of the full R&D cycle: reading papers, prototyping algorithms, making proof of concept demonstrations. You will have the opportunity to work on advanced applied deep learning projects, implement and improve on state-of-the-art methods, work in a team with the same interests.


You should apply if you are a software engineer who is fairly comfortable with linear algebra, basic statistics, and the basics of stochastic gradient descent. Experience in machine learning is highly valued, but we do not expect proficiency in deep learning — since the tasks we try to develop are somewhat at the edge of state-of-the-art, we trust that nobody's an expert.

Job requirement

  • Fairly comfortable with linear algebra, calculus, statistics, and the basics of numerical optimization (e.g. stochastic gradient descent, second order methods etc.)
  • Programming skills to prototype and test ideas - proficiency in at least one programming language (C, C++, Python, MATLAB) - preferable Python
  • Machine learning (Neural Networks) knowledge
  • Experience with machine learning frameworks like TensorFlow, Caffe, Theano, PyTorch
  • Objective achievements in another field, such as creating a large software system, awards in international math/science/programming contests. (optional)
  • Know your way around a Unix shell
Would be a plus:
  • MSc / PhD in mathematics, machine learning, image or signal processing
  • Track record of coming up with new ideas in machine learning (publications or projects)