Computer Vision Engineer

Role Overview

Join the Computer Vision team at Senquire Analytics responsible for the intelligence behind EaglAI’s automated quality-inspection systems. You will own the complete Vision AI journey for industrial deployments—from selecting the right combination of cameras, vision hardware, and models to achieving the required inspection accuracy and commissioning the solution on the factory floor.

Responsibilities

• Own the end-to-end Computer Vision and AI solutioning for each customer deployment, from understanding the inspection requirement through model selection, validation, commissioning, and production acceptance.
• Translate customer quality requirements into measurable AI performance targets and take responsibility for delivering the required accuracy, reliability, false-accept, and false-reject rates.
• Select the appropriate Computer Vision models, image-processing techniques, and inference strategies for different inspection applications and combinations of cameras.
• Collaborate with Computer Vision and Automation engineers to define the optimum vision hardware for each project, including cameras, lenses, lighting, triggering, mounting, and computing requirements.
• Design and govern image-capture, dataset-curation, annotation, training, validation, and model-evaluation procedures.
• Guide and manage junior engineers responsible for image collection, annotation quality, model training support, testing, and performance evaluation.
• Integrate, configure, and troubleshoot Computer Vision models within the EaglAI software suite, working effectively with its Linux and C based technology stack.
• Travel to customer manufacturing sites and take ownership of the AI and Computer Vision commissioning of automated quality-inspection machines.
• Monitor deployed model performance and manage model updates, retraining, validation, release, rollback, and traceability.

Requirements

• Proven experience in end-to-end Computer Vision solutioning and model deployment.
• Ability to work with Linux and C based technology stacks.
• Experience in selecting and configuring vision hardware including cameras, lenses, and lighting.
• Strong understanding of dataset curation, annotation, and model evaluation procedures.
• Willingness to travel to customer manufacturing sites for commissioning.

Skills

• Python
• OpenCV
• PyTorch
• Linux
• C