Machine Vision Engineer - Smart Automation & Imaging

Piper Companies

Raleigh (NC)

On-site

USD 90,000 - 140,000

Full time

2 days ago
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Benefits offered by this job

Medical benefits
Dental benefits
Vision benefits
401K

Job summary

Piper Companies seeks a Machine Vision Engineer to join an innovative organization in the agricultural technology and automation field. This is an onsite permanent position based in Raleigh, NC, bridging research initiatives and commercial operations for a global customer base.

The engineer will support and enhance imaging and automation platforms, collaborating with engineering, R&D, and field service teams to resolve issues, improve ML models, and analyze data to drive product innovation in

Qualifications

  • Bachelor's degree or higher in a technical field.
  • Experience implementing computer vision, ML, or image processing in production.
  • Understanding of automated equipment, robotics or industrial systems.

Responsibilities

  • Support and optimize computer vision applications on automated production equipment.
  • Collaborate with engineering, R&D, and field service teams to resolve vision system issues.
  • Improve models and software to increase accuracy, efficiency and scalability.
  • Analyze operational data to recommend enhancements for product innovation.
  • Assist with customer deployments and validation of new vision capabilities in production.

Skills

Computer vision
Machine learning
Image processing
Troubleshooting
Cross-functional communication
Analytical thinking

Education

Bachelor's degree in Computer Science or Computer Engineering

Tools

Python
C++
OpenCV

Job description

Piper Companies seeks a Machine Vision Engineer to join an innovative organization in the agricultural technology and automation field. This is an onsite permanent position based in Raleigh, NC, bridging research initiatives and commercial operations for a global customer base.

The engineer will support and enhance imaging and automation platforms, collaborating with engineering, R&D, and field service teams to resolve issues, improve ML models, and analyze data to drive product innovation in

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