Computer Vision Engineer

Hiring for a USA based multinational Software Company

We are seeking a talented Computer Vision Engineer to join our team and develop innovative solutions using cutting-edge AI and image processing technologies. The ideal candidate will have strong experience in computer vision, machine learning, and deep learning frameworks to build real-world applications such as object detection, facial recognition, image segmentation, and visual analytics.

• Design, develop, and implement computer vision algorithms for image and video analysis.
• Work with datasets to train, test, and validate deep learning models using frameworks like TensorFlow, PyTorch, or OpenCV.
• Build and optimize object detection, tracking, and recognition systems.
• Collaborate with cross-functional teams including data scientists, ML engineers, and software developers.
• Perform model evaluation, optimization, and deployment on cloud or edge devices.
• Research and stay updated on the latest advancements in AI, deep learning, and computer vision technologies.
• Write efficient, maintainable, and well-documented code.
• Proven experience with Computer Vision and Deep Learning frameworks (TensorFlow, Keras, PyTorch).
• Strong knowledge of Python, OpenCV, and image / video processing techniques.
• Experience with CNNs, object detection (YOLO, Faster R-CNN, SSD), segmentation (U-Net, Mask R-CNN).
• Familiarity with NVIDIA CUDA, GPU acceleration, and model optimization tools.
• Understanding of data preprocessing, annotation, and augmentation methods.
• Excellent analytical, problem-solving, and debugging skills.
• Experience with real-time computer vision systems or edge AI (Jetson Nano, Raspberry Pi).
• Knowledge of 3D vision, SLAM, or AR / VR technologies.
• Familiarity with cloud platforms (AWS, Azure, Google Cloud) and MLOps workflows.
• Contributions to open-source computer vision projects are a plus.

Skills Required

object detection , Machine Learning, Segmentation, Tensorflow, Pytorch, Raspberry Pi, Python, Aws, ssd, Google Cloud, Deep Learning, 3D Vision, Augmentation, Annotation, AR, MLops, Opencv, Keras, Vr, Azure, Computer Vision