Pozent Corporation
Role Overview
Develop and deploy computer vision solutions using deep learning, image processing, and modern CV frameworks. Build production-ready systems for visual understanding and analysis.
Responsibilities Design and implement computer vision models for object detection, segmentation, and classification Develop image processing pipelines for enhancement, filtering, and feature extraction Build and optimize CNN architectures for various computer vision tasks Implement CV solutions using OpenCV for real-time image and video processing Train and fine-tune deep learning models using PyTorch for production deployment Optimize models for performance, accuracy, and inference speed Collaborate with cross-functional teams to integrate CV solutions into products Requirements
Bachelor's degree
in Computer Science, Electrical Engineering, AI/ML, or related field Strong expertise in
image processing
techniques and algorithms Proven experience with
CNNs
and deep learning architectures (ResNet, YOLO, U-Net, etc.) Proficiency in
OpenCV
for computer vision applications Hands-on experience with
PyTorch
for model development and training Strong Python programming skills Understanding of computer vision fundamentals (feature detection, image transforms, edge detection) Preferred
Experience with object detection frameworks (YOLO, Faster R-CNN, SSD) Knowledge of semantic/instance segmentation techniques Familiarity with vision transformers (ViT, DETR, SAM) Experience with video processing and tracking algorithms Understanding of 3D vision, depth estimation, or SLAM Knowledge of model optimization (TensorRT, ONNX, quantization) Experience with GPU programming and CUDA Familiarity with cloud deployment and MLOps
Develop and deploy computer vision solutions using deep learning, image processing, and modern CV frameworks. Build production-ready systems for visual understanding and analysis.
Responsibilities Design and implement computer vision models for object detection, segmentation, and classification Develop image processing pipelines for enhancement, filtering, and feature extraction Build and optimize CNN architectures for various computer vision tasks Implement CV solutions using OpenCV for real-time image and video processing Train and fine-tune deep learning models using PyTorch for production deployment Optimize models for performance, accuracy, and inference speed Collaborate with cross-functional teams to integrate CV solutions into products Requirements
Bachelor's degree
in Computer Science, Electrical Engineering, AI/ML, or related field Strong expertise in
image processing
techniques and algorithms Proven experience with
CNNs
and deep learning architectures (ResNet, YOLO, U-Net, etc.) Proficiency in
OpenCV
for computer vision applications Hands-on experience with
PyTorch
for model development and training Strong Python programming skills Understanding of computer vision fundamentals (feature detection, image transforms, edge detection) Preferred
Experience with object detection frameworks (YOLO, Faster R-CNN, SSD) Knowledge of semantic/instance segmentation techniques Familiarity with vision transformers (ViT, DETR, SAM) Experience with video processing and tracking algorithms Understanding of 3D vision, depth estimation, or SLAM Knowledge of model optimization (TensorRT, ONNX, quantization) Experience with GPU programming and CUDA Familiarity with cloud deployment and MLOps