Deep Learning Engineer

Deep Learning, with its impressive accuracy and variety in applications, is driving the current AI boom! Do You want to join us to enable the next wave of advanced Deep Learning powered products?

Deep Learning is driving the current AI boom, from machine vision to playing computer games, outperforming the best humans. AI will change the world as we know it the coming decades. Contrary to what's sometimes depicted in media, there are still many grand challenges in the field waiting for a solution. One of these challenges, and the mission of EmbeDL, is to make Deep Learning more efficient so that it can be deployed everywhere with low cost and low energy consumption. We want to enable the next wave of advanced AI powered applications and we want You to join us in this mission!

The Role

You will be developing the software platform integrating the user, our core technology and the target device. You will work closely with the research team to make sure that our state-of-the-art algorithms are packaged as a professional software product. More specifically, some of your challenges will be:

  • Automated parsing of user models from Deep Learning frameworks like TensorFlow and PyTorch
  • Increased Deep Learning Inference Hardware support
  • Software deployment, integration and security

Who are you?

We are looking for an outstanding software developer with excellent problem solving skills that can help us to deliver a moden and high quality software product. You are ambitious, self-driven and thrive when given high-level responsibilities and problems to solve. You should be a team player, willing to both learn from others and teach others, and generally contribute to a positive working environment. It is a plus if you have hands-on experience with Deep Learning tools, but it is not mandatory nor the focus of this position.This position is a software developer role, where you will be exposed to the latest within AI, but the role is to develop the software packaging and delivering infrastructure for the product. If you want to do R&D in Deep Learning we have other open positions focused on just that. 

    You must have

  • M.Sc. or PhD in Computer Science, Physics, Electrical Engineering, or make a great case for your equivalent skills achieved via experience (good grades required)
  • Excellent coding skills in Python and C/C++
  • 3+ years industry experience developing software, preferably in the automotive, telecom or other sector where code quality is of great importance
  • Passionate about agile development, release management, continuous integration, testing, git, docker and writing testable and maintainable code
  • Proficient in an UNIX environment and using git and docker

    We would be super-happy if you also have

  • Experience with FPGA, ASIC design or embedded programming
  • Hands-on experience with Deep Learning tools in industry, university or a hobby-project

Who are we?

EMBEDL AB (EmbeDL) is a spin-out from the European Commission Horizon 2020 funded research project LEGaTO. The mission of EmbeDL is to develop and commercialize its Deep Learning optimization engine into a highly scalable platform that makes DL-based AI affordable and energy efficient in embedded systems. The DL optimization engine bridges the gap between data scientist (experts in AI algorithms) and computer engineers (experts in hardware).

EmbeDL has close connections to academic research, Swedish industry and innovation ecosystem as well as well-established connections to venture capital.

Application process

The selection and interview process is ongoing. Therefore, please send in your application in English as soon as possible. For any questions and clarifications connect or reach out to

You are welcome at EmbeDL for who you are, no matter where you come from, what you look like, or what’s your favourite IDE.

Or, know someone who would be a perfect fit? Let them know!


Mässans gata 10
412 51 Göteborg Directions View page

Workplace & Culture

We have a very flat organization where every colleague bring their specific expertise and experience in the decision making. A lot of what we do is bleeding edge research, so there is no failures, only new findings to learn and grow from.  



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