We use cookies on our site to track usage and preferences. Learn more

R&D Engineer – Machine Learning & Image Processing

  • Closing date 30 Jun 2018
  • Type Full-time
  • Duration Permanent

Spectral Edge is a specialist in image processing and computational photography. The company uses patented image fusion algorithms in combination with state of the art machine learning techniques to solve challenging image processing problems, including multi spectral fusion and multi sensor registration among others.  

We are growing fast and are looking for an R&D engineer experienced in Machine Learning & Image Processing technologies.

 

You should have knowledge of Machine Learning techniques in the field of Image Processing, with experience in Object Detection techniques (DarkNet, Yolo, SSD) and Neural Network frameworks (Tensorflow, Caffe). The core of this exciting role is to apply Machine Learning techniques to Image Processing problems as required, by defining the architecture, preparing the training set, training the system and evaluating the results.

The key duties are:

•  R & D in the computational photography field, using machine learning techniques as appropriate to various problems including the areas of interpolation, registration and tone mapping

•  In conjunction with our software and hardware teams, deploy the processing units based on machine learning as hardware or software IPs

 

The key skills are:

•  Strong Python, C/C++ skills and a working knowledge of Matlab

•  Familiarity with Image Processing algorithms and Image Quality procedures & criteria

•  Strong mathematical background. Master’s degree or above in Maths or Computer Science expected

•  Good communication and team-working skills

The following additional skills would be an advantage:

•  Experience of GPUs and languages such as OpenGL/CL, CUDA

•  Knowledge of image processing algorithms, e.g de-noising or image registration algorithms

Contact us

Thank you for your enquiry!
We'll be in touch soon.

We couldn't send your message.
Please review the fields then try again