Python Engineer

Model Development & Deployment: Design and implement deep learning models using TensorFlow for real-time object detection, image segmentation, and video processing tasks.

Computer Vision Expertise: Leverage advanced computer vision techniques, including CNNs, YOLO, Faster R-CNN, and SSD for object detection in images and video.

Video Processing: Process and analyze video streams, including motion tracking, behavior analysis, and real-time video object detection using frameworks like OpenCV.

Data Preparation: Clean, preprocess, and augment large-scale image/video datasets to improve model accuracy and performance for training.

Model Optimization: Optimize machine learning models for real-time performance, focusing on latency reduction and efficient resource utilization.

Integration with Systems: Collaborate with cross-functional teams to integrate trained models into production environments, such as edge devices or cloud platforms.

Performance Tuning: Use techniques like model pruning, quantization, and edge deployment to enhance model efficiency and scalability.

Research & Innovation: Stay up-to-date with cutting-edge research in AI, computer vision, and TensorFlow, and apply the latest advancements to solve complex problems.

Collaboration & Code Quality: Work in an agile, collaborative environment while writing clean, maintainable code and documenting the model development process.

Required Skills: Proficiency in Python, TensorFlow, OpenCV, machine learning, and deep learning, with experience in object detection and video processing.

1. Tensorflow 2. Computer Vision 3. Video processing 4. Object detection