Computer Vision Engineer (offline)

Requirements:
— Strong knowledge in computer vision fundamentals i.e. OpticalFlow, HOG, feature detection algorithms, Hough Transform, Haar Cascades, Homography, Morphology, Denoising/Deblurring, and image processing algorithms.
— Strong Python knowledge
— Strong practical experience with DL/CV frameworks like OpenCV, PyTorch, MXNet, Tensorflow, or Keras
— Experience with some of the well-known neural networks architectures such as Yolo, MobileNet, U-Net, R-CNN-based architectures;
— Understanding state-of-the-art CV approaches for problems like object detection/tracking, video analysis, semantic segmentation, pose estimation, optical character recognition
— Upper-intermediate level of English mandatory

Would be a plus:
— Experience with R, C++
— Experience with following modern neural network architectures: LSTM and other RNN-based, Tranformers(BERT etc.).
— Familiarity with time-series predictive/anomaly detection analyses, natural language processing, signal processing
— Understanding SOTA approaches for machine learning problems like unsupervised / semi-supervised learning.
— Experience with the following DL frameworks: DLib, Darknet, Theano.
—Awareness of CRISP-DM process model
— Experience with continuous integration and release management tools, preferably within the AWS platform.
— Hands-on Experience with the common architecture of MLOps system by the means of Hadoop, Docker, Kubernetes, cloud services and experience with managing production ML lifecycle

About CHI Software

CHI Software teams leverage the best practices to cover all development process and provide cutting-edge solutions. Our experts can work as a part of an extended team, or a dedicated team to achieve business goals and objectives.

Company website:
https://chisw.com.ua/