Industrial Vision Engineer for Smart Manufacturing

Lyten

Västerås kommun

On-site

SEK 750,000 - 1,100,000

Full time

14 days+

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Job summary

Lyten is seeking a Vision Engineer to develop, integrate, and improve machine vision for manufacturing equipment. You will collaborate across production, process, quality, and software teams to build robust vision solutions for inline and offline processing.

You will ensure high availability and reliability of vision systems, support calibration, testing, and data analysis, and drive enhancements based on system metrics to optimize production outcomes.

Qualifications

  • Bachelor's or Master's degree in software/engineering or related field.
  • 5+ years writing production-grade C/C++, Python, or Go.
  • Experience with real-time vision systems and OpenCV.

Responsibilities

  • Collaborate with cross-functional teams to define vision system requirements.
  • Install, configure, and calibrate vision systems for MES integration.
  • Develop test plans and validate performance in manufacturing.
  • Analyze vision data and implement optimization improvements.
  • Provide ongoing support, calibration, and troubleshooting for vision systems.
  • Organize internal training and participate in workshops.
  • Provide cost estimations and input for project quotes.

Skills

C/C++
Python
Go
OpenCV
Computer vision
Git basics
Vision systems hardware
Machine learning for vision
English proficiency

Education

Bachelor's or Master's in Software Engineering, Electronics/Computer Engineering, Information Systems, or related field

Tools

MES integration

Job description

Lyten is seeking a Vision Engineer to develop, integrate, and improve machine vision for manufacturing equipment. You will collaborate across production, process, quality, and software teams to build robust vision solutions for inline and offline processing.

You will ensure high availability and reliability of vision systems, support calibration, testing, and data analysis, and drive enhancements based on system metrics to optimize production outcomes.

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