Computer Vision Engineer (The Visual Intelligence Architect)

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Requirements:

• Strong knowledge of computer vision techniques, including object detection, image segmentation, optical flow, 3D reconstruction, and facial recognition.
• Experience with deep learning models like CNNs, ResNet, YOLO, and EfficientNet.
• Proficiency in Python and experience with computer vision libraries like OpenCV, TensorFlow, and PyTorch.
• Expertise in processing large datasets and image preprocessing techniques.
• Experience deploying models using cloud platforms like AWS or Azure, familiarity with Docker and Kubernetes is a plus.
• Interest in applying new research and improving existing models.
• Bachelor's or Master's degree in a relevant field or equivalent experience.
• 3+ years of experience in computer vision engineering with a track record of deploying models.
• Hands-on experience with large-scale image and video datasets.

Responsibilities:

• Develop and optimize computer vision algorithms using state-of-the-art techniques such as CNNs, image segmentation, object detection, and facial recognition.
• Preprocess and analyze image and video data to accurately detect and classify objects, track motion, and recognize patterns.
• Train deep learning models for tasks like object detection and image classification, optimizing hyperparameters for real-world deployment.
• Deploy computer vision models into production, ensuring they are scalable and integrated with real-time systems.
• Evaluate model performance using metrics like accuracy and precision, and monitor models in production to maintain high performance.
• Collaborate with cross-functional teams to develop solutions that align with product goals and deliver real-world value.
• Stay updated on the latest research in computer vision and deep learning, experimenting with new techniques as applicable.