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Computer Vision Engineer – Deep Learning


Up to $180k

We are looking for multiple Computer Vision Engineers to create Vision focused Machine Learning / Deep Learning algorithms to be deployed on a range of bleeding-edge projects across the likes of 3D reconstruction, motion detection, and object recognition that will help shape an entire industry.

Working within this environment would allow you to join forces with a team that has 20+ years of experience and is recognized as a truly world-leading team when it comes to Deep Learning & Computer vision research

The research team is central to making this organization the best AI company on the planet and work on the core underpinning AI, they continuously aim to push the bar and work with bleeding-edge technology & techniques to achieve the impossible. This team looks beyond the latest techniques in Deep Learning to what is next.

You will be collaborating with diverse teams not only within the organization but also within the academic world which will allow you to stay up to date and allow you to publish and present your work at all the top-tier conferences & journals.

Requirements

  • Ph.D. in Computer Science/Engineering, Machine Learning, Computer Vision, Robotics, or a related field.
  • 3+ years of research and development experience within Computer Vision, Deep Learning or statistical modeling
  • Published research papers in relevant conferences (e.g., CVPR, ECCV, ICCV, ICML…).
  • Exceptional knowledge and development experience with Deep Learning frameworks such as Tensorflow & PyTorch.
  • Experience with implementation of Deep Learning algorithms on real-world vision projects such as action recognition, object tracking & detection, 3D pose estimation, etc…
  • Excellent software programming skills in Python and C++.
  • A vested interest in intensive research that has real-world impacts.
  • Strong communication skills, you need to be organized and self-motivated.

For a confidential conversation, please respond to this advert or send an up to date CV to [email protected]

Contact:
John Stephenson

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