Advanced Computer Vision Model Developer

2 weeks ago

Karachi, Sindh, Pakistan beBeeVision Full time
Computer Vision Engineer

We are seeking a highly skilled Computer Vision Engineer to join our team and contribute to the development of AI-driven object detection, segmentation, and pose estimation models. The successful candidate will have a strong background in computer vision and machine learning, with hands-on experience in developing and optimizing computer vision models for real-world applications.

The ideal candidate will have expertise in object detection, segmentation, and pose estimation, as well as experience with industry-standard models such as YOLO, Detectron, and Mask R-CNN. They will also have a deep understanding of Visual Language Models (VLMs) and the ability to develop event analysis solutions from videos.

A strong proficiency in Python, TensorFlow, PyTorch, and OpenCV is required, as well as experience in deploying models in cloud-based and edge environments. The successful candidate will be able to work collaboratively with cross-functional teams to integrate models into smart security and surveillance solutions.

This role requires a Mid-Senior level professional with a passion for working on cutting-edge projects and delivering high-quality results under tight deadlines.

The ideal location for this role is Karachi Division, Sindh, Pakistan.

  • Key Responsibilities:
  • Develop and optimize computer vision models for real-world applications, including object detection, segmentation, and pose estimation.
  • Implement ML pipelines for model training, evaluation, deployment, and post-production improvements based on user feedback.
  • Work on Visual Language Models (VLMs) to develop advanced vision-based analysis—understanding what's happening in videos and assessing the severity of events.
  • Deploy models on production servers, optimize for scalability, and improve system performance. Collaborate with the AI/ML team to continuously enhance model accuracy and robustness.
  • Requirements:
  • Strong expertise in object detection, segmentation, and pose estimation.
  • Experience with YOLO, Detectron, Mask R-CNN, and other industry-standard models.
  • Hands-on experience with ML pipelines for vision models, from training to deployment and retraining based on real-world feedback.
  • Deep understanding of VLMs (Visual Language Models) and ability to develop event analysis solutions from videos.
  • Proficiency in Python, TensorFlow, PyTorch, OpenCV and related frameworks.
  • Experience in deploying models in cloud-based and edge environments.
  • Benefits:
  • Possibility of getting 2x chances of interviewing at IRVINEi by referral.

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