Computer Vision Engineer

The Role

We are looking for candidates to contribute to two of our flagship projects in deep-tech areas of computer vision, AI/ML, and sensor technology.

1. Drivers alert management system (DAMS).

2. Quality management in textile Industry.

Responsibilities:

• Design and implement real-time computer vision pipelines for diverse applications, including driver drowsiness detection and automated textile defect inspection, covering image/video preprocessing, feature extraction, and object detection/classification.

• Develop, train, and fine-tune deep learning models using frameworks like PyTorch, TensorFlow, or OpenCV, employing CNNs for facial/eye/mouth analysis and advanced architectures (e.g., segmentation or anomaly detection networks) for textile defect identification.

• Develop on-loom inspection solutions in textile manufacturing, handling high-resolution, continuous streaming data and implementing efficient defect detection and pattern recognition algorithms suitable for industrial settings.

• Conduct rigorous model evaluation and benchmarking, ensuring high accuracy, low false positives, and real-time performance under varying conditions.

• Optimize models and pipelines for real-time inference, including lightweight architectures, quantization, and GPU/edge acceleration techniques.