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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

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📌 AI Vision Engineer 2 (N) (Centro)
🏢 Sanmina
📍 Centro