Computer Vision Data Science Engineer

Job Description

Job Description for Computer Vision Data Science Engineer Role Apply About the Role: We are seeking an experienced Data Science Engineer specializing in computer vision to join our innovative team. The ideal candidate will have a strong background in developing and implementing advanced computer vision solutions, with particular expertise in number plate recognition, face recognition, YOLO object detection, and NVIDIA DeepStream. Responsibilities: Design, develop, and optimize computer vision algorithms for real-time video analytics Implement and fine-tune deep learning models for object detection, face recognition, and number plate recognition Utilize YOLO (You Only Look Once) architecture for efficient object detection in video streams Leverage NVIDIA DeepStream SDK to build and deploy AI-powered video analytics applications Collaborate with cross-functional teams to integrate computer vision solutions into existing systems Conduct performance analysis and optimization of computer vision models Stay current with the latest advancements in computer vision and deep learning technologies Requirements: Masters or Ph. D. in Computer Science, Data Science, or related field 3+ years of experience in computer vision and deep learning Proven experience with number plate recognition and face recognition systems Strong proficiency in YOLO object detection framework Hands-on experience with NVIDIA DeepStream SDK Expertise in Python and relevant computer vision libraries (OpenCV, TensorFlow, PyTorch) Experience with GPU acceleration and optimization techniques Solid understanding of machine learning principles and statistical analysis Excellent problem-solving skills and attention to detail Strong communication skills and ability to work in a collaborative environment Preferred Qualifications: Experience with edge computing and embedded systems for computer vision Familiarity with video compression techniques and streaming protocols Knowledge of privacy-preserving machine learning techniques Experience with cloud-based deployment of computer vision models Contributions to open-source computer vision projects