Technology Department (CTO)

Machine Learning Engineer Internship

Preferable Location(s): Johannesburg, South Africa | Cape Town, South Africa
Work Type: Internship
Machine Learning Engineer Internship

Duration: 12 months (Including a 3-month probation period) 

Location: Office-based position in Johannesburg 


We are seeking a Machine Learning Engineer Intern to assist with the development and maintenance of our machine software applications. This may extend past machine learning to traditional software engineering. In this role, your duties will include reporting to your mentor, collaborating with colleagues, and ensuring we deliver the best possible solutions and services to our clients.


Skills:

  • Python
  • Strong software development fundamentals
  • Deep Learning
  • Experience with at least one of Tensorflow, Pytorch

Requirements:

Matric/Standard 10/NQF 4

A stable internet connection if not based in Gauteng.

Willingness to learn coupled with humbleness in the advent of mistakes.

  • Excellent interpersonal, logical, and problem-solving skills

Good communication and self-organization skills

Candidates not in the process of completing a STEM degree will need a strong project portfolio to be considered.


Nice to haves:

  • Experience with Computer Vision
  • Academic coursework in computer science, statistics, or machine learning
  • Experience with a compiled language such as Java or C++

Some benefits of interning at Sybrin:

  • Competitive stipend
  • Close mentorship from our experienced engineers
  • The opportunity to work on projects with impact in Africa and beyond
  • Exposure to multiple industries within the financial services sector
  • A work itinerary carefully catered to the intern’s learning goals
  • Fully remote work, with the option of coming into the Montecasino office.
  • Possibility of future employment

What are some of the tasks you may get to work on?

  • Liveness detection
  • Facial recognition
  • Document segmentation
  • Optical character recognition (OCR)
  • Data Preparation and collection for the above


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