Description:
ROLE AND RESPONSIBILITIES:
- Develop efficient Computer Vision Algorithms for tasks such as object detection, recognition, image segmentation, and tracking.
- Create advanced models and pipelines for image and video analytics.
- Design, train, and optimize Machine learning models using frameworks like TensorFlow, PyTorch, TfLite or Keras.
- Implement Deep learning techniques, including CNNs, RNNs, and Transformers, to enhance visual recognition systems.
- Write robust software to integrate sensors such as cameras, LiDAR, or other input systems into vision solutions.
- Collaborate with cross-functional teams to embed vision systems into broader product architectures.
- Test, validate, and refine models on real-world datasets to ensure high accuracy and efficiency.
- Deploy models on cloud platforms, edge devices, or embedded systems, ensuring scalability and reliability.
- Stay updated with the latest advancements in computer vision, 3D vision techniques (e.g., SLAM), and machine learning technologies.
- Conduct research to identify new opportunities for applying AI vision in innovative ways.
- Work closely with engineering and product teams to design and implement integrated vision systems.
QUALIFICATIONS REQUIREMENTS:
- Minimum BSCS, BSIT, BSSE with 1+ years of experience as a AI Computer Vision Engineer