Computer Vision Engineer Jobs
HOW TIETALENT WORKS

#1 Let us know about you
Tell us what you are looking for, your skills and aspirations.

#2 Companies apply to you
Once you get matched with companies interested in your profile, you will be able to respond to interview requests.
Setup your interviews and we will provide you with adequate guidance.

#3 Get hired
Receive job or freelance mission offers and choose the one that interests you the most.
Find Computer Vision Engineer jobs in Switzerland and Germany
Computer vision is a field in computer science – more specifically, artificial intelligence. It enables computers to process, interpret, and understand the visual world in the same way that a human would. The computers can subsequently react to what they have “seen”.
Computer vision engineers can pursue two broad career paths: working as software developers to create vision algorithms for pattern recognition, or using computer vision software in the development of applications.
In more detail
Computer vision can be implemented in a number of different fields, such as medicine, manufacturing, retail, healthcare, banking, and more. However, the main task of computer vision engineers, which is a constant for all computer vision engineer jobs, is developing algorithms.
Some things that computer vision accomplishes are object recognition, tracking, localisation, reconstruction, and understanding. Frequently, engineers will be responsible for working on multiple of these areas at once. All of these have many practical uses and help solve real-world problems.
In order to pursue a career in this relatively new field, software engineering skills are essential. Some commonly used languages for developing computer vision algorithms are C++ and Python. Therefore, it is a good idea to learn these in-depth. Generally, companies seek candidates with at least a bachelor’s degree in Computer Science, Electrical Engineering, Math, or related fields. However, a master’s degree is preferred.
Some universities even offer specialisations in computer vision itself, which would be an advantage for candidates wishing to find work in this field.
Otherwise, knowledge of traditional machine learning is extremely important, as is a good understanding of linear algebra, probability, and statistics.
Experience with computer vision tools such as OpenCV is extremely beneficial, as is familiarity with deep learning frameworks such as TensorFlow and PyTorch.
Analytical thinking skills are necessary for this field, as working on computer vision often involves solving complex problems.