AI Vision Engineer 2 (N)

Sanmina; Región Centro; Presencial; MXN 300.000 - 420.000; Jornada completa

Descripción de la vacante

Sanmina is seeking a Software QA Engineer 2 who can drive the end-to-end development of computer vision solutions for manufacturing lines. The role covers data collection, model training, and integration with on-site hardware and software for real-time analytics.

The ideal candidate will have hands-on experience with deep learning for CV, edge AI deployment on Jetson platforms, and proficiency with NVIDIA TAO and DeepStream tools.

Formación

• Proven experience in designing and training deep learning models for computer vision tasks.
• Strong experience with image processing, object detection, and image segmentation.
• 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 transfer learning to adapt models for factory tasks.
• Deploys real-time video analytics applications using NVIDIA DeepStream SDK.
• Begins to use NVIDIA Omniverse for visualizing factory layouts in a simulated 3D environment.

Responsabilidades

• Owns the full lifecycle of vision projects from data acquisition to production integration.
• Design, train, and deploy computer vision models for manufacturing applications.
• Optimize and validate models on edge devices and production systems.
• Collaborate with hardware and software teams to ensure seamless deployment.

Conocimientos

Deep learning

Computer vision

Image processing

Object detection

Image segmentation

Transfer learning

Edge AI deployment

Herramientas

NVIDIA Jetson Orin

NVIDIA TAO Toolkit

NVIDIA DeepStream SDK

NVIDIA Omniverse

Descripción del empleo

Job Description

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