Machine Learning Intern - Paid

AI · Edmonton, Alberta
Department AI
Employment Type Full-time, Internship

About Medo:

MEDO is attempting to democratize medical imaging by providing patients with efficient and affordable ultrasound expertise at the point of care. We use machine learning systems to radically simplify the way ultrasound scans are performed and interpreted, enabling all caregivers to make an accurate and confident diagnosis.

We are dual-headquartered in Singapore and Edmonton AB, Canada, with a team of over twenty clinicians, researchers, and developers who design and build software-as-a-medical-device (SaMD) products. We are backed by Wavemaker Partners as part of the Draper Venture Network, along with SG Innovate and major tech investors in the Asia-Pacific. Our innovations are currently being piloted in over 12 hospitals in 6 countries.

The successful hire will work with a multidisciplinary team of scientists, clinicians, and engineers who are creating artificial intelligence technologies to impact the lives of millions around the world.


  • Undergraduate or Graduate degree in Computer Science or similar disciplines
  • Proficient in Python
  • Background in Machine Learning and Computer Vision
  • Experience with Deep Learning libraries such as PyTorch and TensorFlow
  • Strong knowledge and understanding of CNNs and classic image processing techniques
  • Prior experience with medical image data is desirable (The ideal candidate would have experience working with ultrasound image data)
  • Excellent verbal and written communication skills
  • Able to effectively self-manage workload and handle changing priorities in a startup environment


  • Taking on solo projects where you will utilize machine learning techniques to solve problems
  • Assisting other team members with ongoing projects in any stage, labeling data, research, implementation, etc
  • Working on multiple problems related to different products semi-simultaneously
  • Investigating state-of-the-art networks/methods and implementing a set of candidate approaches for a given project
  • Presenting the discovered solution and the results in a way that could be easily integrated into the main application

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  • Location
    Edmonton, Alberta
  • Department
  • Employment Type
    Full-time, Internship