Responsibilities:
Image classification and recognition, face recognition, key point detection, image processing
Optimize computer vision-related algorithms to improve model accuracy and computing efficiency, so that models can run efficiently at the edge where computing power is limited and achieve accuracy rates that meet scene requirements
Requirements:
Bachelor's degree or above, math, computer-related majors, preferably from a prestigious school; familiar with Linux operating system, computer network, etc., solid basic knowledge
In-depth understanding of deep learning models
strong hands-on skills, ACM, ICPC, NOI/IOI, top coder, and Kaggle competition winners are preferred, experience in image video understanding, image classification, object detection, automatic data labeling, face detection, and recognition algorithms are preferred
Proficiency in Python, at least one framework among Caffe/Pytorch/Mxnet/Tensorflow, C++ programming ability is preferred