We are seeking a highly skilled and innovative Computer Vision Expert to join our AI/ML team. The ideal candidate will design, develop, and deploy computer vision solutions to solve real-world problems using image and video data. This role requires a strong background in machine learning, deep learning, and computer vision, with hands-on experience in building production-grade systems.

Key Responsibilities:

• Design and develop end-to-end computer vision models for object detection, image segmentation, classification, tracking, OCR, and 3D vision.
  

• Work with large-scale image/video datasets, including data collection, cleaning, annotation, and augmentation.
  

• Optimize and deploy models to production on edge devices, cloud platforms, or embedded systems.
  

• Collaborate with cross-functional teams including software engineers, product managers, and domain experts to integrate vision solutions.
  

• Stay current with the latest research in computer vision and deep learning, and apply relevant techniques to existing projects.
  

• Conduct experiments, analyze performance metrics, and iterate quickly to improve model accuracy and robustness.
  

Requirements

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. PhD is a plus.
  

• 3+ years of hands-on experience in computer vision and deep learning.
  

• Proficient in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
  

• Strong understanding of classical computer vision techniques (OpenCV, feature extraction, image processing).
  

• Experience with neural networks for image classification, object detection (YOLO, Faster-RCNN, SSD), and segmentation (UNet, Mask-RCNN).
  

• Experience with model optimization and deployment tools such as TensorRT, ONNX, or OpenVINO.
  

• Familiarity with cloud services (AWS, Azure, GCP) and containerization (Docker, Kubernetes) is a plus.
  

Preferred Skills:

• Experience working with video analytics or real-time processing.
  

• Familiarity with edge AI and embedded systems (e.g., NVIDIA Jetson, Coral).
  

• Contributions to open-source computer vision projects or research publications.