— At least 3 years of experience in Сomputer Vision and/or Deep Learning for object detection and tracking along with semantic or instance segmentation either in academic or industrial domain;
— Proficiency with edge computing principles and architecture preferably for NVIDIA Jetson devices and Raspberry Pi;
— Proficiency in Python and related packages like Numpy, Scikit-learn, OpenVC as well as ML frameworks like PyTorch, Tensorflow, Keras;
— Experience in different model optimization techniques for deploying on low-end edge devices;
— Exposure to IoT technology;
— Excellent written and verbal communication skills for effectively communicating with the team and ability to presenting information to varied technical and non-technical audience;
— BS.c. or MS.c. in Computer Science, Data Science, Machine Learning or in related fields preferred with strong technical knowledge and experience in Computer Vision;
— At least Intermediate level of English.
— Experience with C++ and system-level engineering;
— Experience with classical computer-vision;
— Experience in real-time/embedded systems or performance optimization;
— Interest in patents and research papers.
— free English courses;
— access to company’s library;
— free access to the corporate Udemy account;
— possibility to participate and share your knowledge as a speaker in our internal meetups.
— 100% paid vacation and sick leaves;
— health insurance;
— assistance in relocation;
— free accountant services.
— Developing and maintaining Machine Learning / Deep Learning models and integrating them with classic Computer Vision methodologies;
— Data crunching and analyzing of large datasets, to produce insights for both algorithmic advancements and product development;
— Work with data engineers to scope the data sets and annotation needed;
— Optimize ML/DL models for low-end devices.
Our company invites Algorithms Engineer to join the experienced team and work on computer-vision and machine-learning.
You will become a part of a highly professional team working in the field of smart sensors and IoT for the futuristic public smart spaces.
The task at hand is to establish a pipeline for continuous design, training and evaluation of new models for people/object detection and tracking and further deployment of these models to the edge device.
Technologies: Python, Machine Learning, Deep Learning.Computer Vision.