Kennedy Pearce recruits talented Computer Vision Engineers who specialise in developing AI-powered systems that enable machines to interpret and understand visual data.
Typical responsibilities for Computer Vision Engineer roles include:
Designing and implementing computer vision models for object detection, recognition, segmentation, and tracking
Developing algorithms using frameworks like OpenCV, PyTorch, TensorFlow, or Keras
Training deep learning models such as CNNs, R-CNN, YOLO, and Transformer-based architectures
Working with image, video, and 3D data from diverse sources including cameras, sensors, and LIDAR
Preprocessing and augmenting datasets to improve model performance and generalisation
Deploying computer vision models to production environments using Docker, Kubernetes, or cloud platforms like AWS, Azure, and GCP
Collaborating with data scientists, software engineers, and hardware teams to build end-to-end solutions
Conducting experiments to improve accuracy, reduce latency, and optimise resource usage
Applying computer vision to real-world use cases in areas such as facial recognition, robotics, medical imaging, and autonomous systems
Kennedy Pearce places Computer Vision Engineers with expertise in machine learning, image processing, and production deployment of AI solutions that enhance automation and user experience.
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