We are looking for a strong project manager to join our team of gifted researchers and engineers. You will be responsible for planning, R&D process as well as project delivery.
We are looking for a dedicated machine learning engineer with a strong mathematical background and a proven track record in real projects. You will be involved in all stages of the development process: from R&D to production. You will work with different types of data including images and video, audio, speech, and text.
We are excited to take part in the Kharkiv IT Cluster activity for students! Our CEO, Ievgen Gorovyi, will deliver a talk on “AI progress, or who you will become when you grow up” on April 8, 2021. The event is free of charge, but preliminary registration is required. In the context of rapid digital transformation, more and more business and life processes are taking place online, or even without human involvement.
Augmented reality has already proven its positive impact on many businesses. One of the latest trends is so-called WebAR. Indeed, what can be easier than just opening the web page for instant immersive experience? The goal of this project was to develop and optimize the image detection and tracking algorithm for AR applications. The main challenge was to make it work directly in the mobile web front-end with all computations done on the edge.
A student that is about to graduate from the university and has not yet made his mind about the career he wants to pursue. A freelancer who has already tried a lot of technologies, knows how he wants to develop himself further and would like to gain experience of working in a company. An experienced IT engineer totally burnt out and aiming to find a new passion. A professional architect (not software one) switching his career entirely.
Automatic floor segmentation can serve many interesting purposes including mixed reality (MR) applications, interior design, entertainment, computation of available space in a room, or indoor robot navigation. In this project, we have been solving a problem of scene understanding and, in particular, determining which pixels of the image belong to the floor. The problem of floor segmentation is a good example of how the same task can be solved with classical computer vision algorithms or deep learning.