Computer Vision Engineer

Easycomm Innovations; United States; Remote; USD 110,000 - 150,000; Full time

Job summary

Easycomm Innovations seeks a hands-on Computer Vision Engineer to design and deploy vision systems on production lines in a food-grade manufacturing facility. You will build counting and verification pipelines, integrate camera feeds with edge AI servers, and ensure robust off-line processing where network is unreliable.

You will contribute to dashboards and mobile app features for on-site monitoring, handle real-world data challenges, and push models from lab into live operation.

Qualifications

• Strong foundation in computer vision, machine learning, and image processing.
• Experience deploying models to edge devices and embedded systems.
• Ability to handle real-world data messiness and edge cases.

Responsibilities

• Engineer computer vision systems that monitor production lines on-site.
• Design and build counting and verification pipelines for goods tracking.
• Integrate camera feeds with edge AI servers for on-device processing.
• Develop safety alert mechanisms for irregularities in production and dispatch.
• Contribute to dashboards showing real-time production and dispatch data.

Skills

Computer vision

Edge deployment

Problem-solving

Tools

Embedded systems

Camera/vision tooling

Image processing libraries

Job description

Batch: 2024/2025/2026/2027.

About the role

• Engineer computer vision systems that monitor production lines at an edible oil, soap, and soya meal manufacturing facility
• Design and build counting and verification pipelines that track goods as they move through the factory
• Integrate industrial camera feeds with edge AI servers to process vision data at the point of capture
• Create algorithms that match physical dispatch against ERP system orders at exit gates and loading dock areas
• Develop safety alert mechanisms that flag irregularities in the production and dispatch workflow
• Build the central verification service that coordinates vision data from multiple camera feeds across the facility
• Contribute to the web dashboard that displays real-time production and dispatch information
• Help develop mobile app features for on-site monitoring and alerts

Working conditions

• You will solve computer vision problems in a live manufacturing environment, not controlled lab settings
• Carton condition varies widely, from pristine to heavily worn and damaged
• Products within the same category look similar, making differentiation challenging
• Pallets arrive wrapped and stacked at high speed on conveyors
• Lighting is often poor and inconsistent across different areas of the facility
• Network connectivity is unreliable, requiring robust edge processing and offline-first design

What you'll need

• Strong foundation in computer vision, machine learning, and image processing
• Experience deploying models to edge devices and embedded systems
• Ability to handle real-world data messiness and edge cases
• Problem-solving mindset for challenging environmental constraints