Software QA Engineer 2   The AI ​​Vision Engineer 2 can independently design, train, and deploy custom computer vision models for specific manufacturing applications. They are responsible for the full lifecycle of a vision project, from data acquisition to integration with production line hardware and software. This role requires a deeper understanding of deep learning architectures and the practical challenges of deploying AI in an industrial environment. Proven experience in designing and training deep learning models for computer vision tasks. Strong experience with image processing, object detection, and image segmentation techniques.1 Hands-on experience deploying and optimizing vision models on NVIDIA Jetson edge AI platforms (e.g., Jetson Orin series). Proficient with the NVIDIA TAO Toolkit, using its transfer learning capabilities to rapidly adapt and fine-tune high-performance models for specific factory tasks.16 Deploys real-time video analytics applications using the NVIDIA DeepStream SDK, which provides a framework for building efficient, high-throughput vision AI pipelines.10 Begins to use NVIDIA Omniverse for visualizing factory layouts and testing camera placements in a simulated 3D environment, improving the design of vision systems before physical installation.20