Research Team Leader (Computer Vision)

Brodmann17 is a provider of software-only perception technology for vision-based automated driving. Brodmann17’s patent-pending deep learning architecture delivers state-of-the-art accuracy while consuming only a fraction of the compute power, expanding the benefits of artificial intelligence found in premium vehicles to the mass market. Brodmann17’s solution is built from the ground up and designed to meet the industry’s toughest standards for the world’s largest automakers and Tier-1 automotive suppliers. Three years into the research and the technology has its first design wins with automotive companies whose products are expected to hit the market as early as this year.

If you want to work in one of the most interesting AI companies led by top technologists  and researchers in this field – join us!

About the Job:

We are seeking a sharp algorithm team leader with a solid understanding in Deep Learning and Computer Vision that will help shape the future of computer vision solutions and lead our research team.

Main Responsibilities:

  • You will plan, design, and carry through short-term applicative challenges as well as long-term research projects.
  • Investigate, identify, and implement novel research ideas 
  • Provide input for future planning based on area of expertise 
  • Be involved on algorithmic challenges as well as visionary project leading, mentoring and advising senior algorithm developers, and training junior developers.



  • MUST Experience in leading a long-term data research projects from vision to implementation.
  • Deep learning for Computer Vision in depth knowledge
  • Familiarity with toolkits for deep learning such as TensorFlow/PyT
  • More than 3 years of experience required as an Applied Machine-Learning / Algorithms Engineer / Computer Vision Engineer
  • MSc  (with thesis) in Computer Science or equivalent is a MUST. A Ph.D. degree is an advantage
  • A team player with good communication skills, both written and verbal
  • Gets things done attitude

Big Advantage:

  • In depth familiarity with deep-learning algorithms for  object detection, segmentation , tracking etc
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