Intern, Applied deep learning in machine vision S-03-15 (Summer 2022)

Type:

Category:

Division: 
Imaging

Location:

Job ID: 
S-03-15

 

Position Summary

Looking for an applied deep learning internship position within a Research and Development team made up of experts passionate about artificial vision? An engineering culture, an open and collaborative environment where all your ideas will be listened to and valued? Matrox’s Imaging division offers you this exciting opportunity to contribute to the improvement of the Matrox Imaging Library (MIL).

MIL is a library of analysis and image processing deployed internationally on hundreds of thousands of industrial machines. Recognized for its performance, robustness and outstanding reliability, MIL solves vision applications with industry leaders. The library makes it possible, among other things, to locate objects, extract and measure their characteristics, classify them, read strings and barcodes, perform 3D reconstruction, and much more.

 

Responsibilities

  • Assimilate state-of-the-art machine learning approaches to design, build and optimize solutions for the machine vision industry.
  • Actively review scientific papers to remain up-to-date with computer vision and machine learning developments.
  • Involved in preparing datasets, training and evaluating deep learning models and algorithms.
  • Document and share findings and results with the R&D teams.

 

Qualifications

  • Graduate-level student in Computer Science, Software Eng., Electrical Eng. or, related field;
  • Extensive knowledge of Deep Learning in applied Computer Vision;
  • Experience with deep learning frameworks like TensorFlow, PyTorch or MxNet;
  • Possess solid programming skills in Python; knowledge of C/C++ is an asset;
  • Image processing / Computer vision knowledge is an asset;
  • Quick learner and passionate to review scientific papers;
  • Have strong team work and documentation skills;
  • Competent in French/English (spoken and written).

 

Documents required when applying

  • Transcript
  • Coverletter
  • CV

Job application

Files must be less than 80 MB.
Allowed file types: txt doc docx pdf.
Files must be less than 80 MB.
Allowed file types: txt doc docx pdf.
Files must be less than 80 MB.
Allowed file types: txt doc docx pdf.