Machine Vision Engineer

About this role

About the role: - Build and refine computer vision systems that power industrial automation and quality control - Design optical configurations tailored to specific inspection and measurement tasks - Develop and optimize algorithms for real-time image processing and analysis - Deploy machine learning models into production environments - Integrate vision hardware with robotic and automated manufacturing systems - Debug and enhance algorithms through profiling and performance tuning What you'll work on: - Optical system design including field of view, working distance, focal length, magnification, depth of field, and pixel-level precision - Calibration workflows, distortion correction, and coordinate transformation logic - Real-time multithreaded image processing pipelines - Integration with industrial camera SDKs and frame-grabber hardware - User interface development for vision applications - Algorithm validation, testing procedures, and code review practices What we're looking for: - Bachelor's or Master's degree in Computer Science, Electronics and Communication Engineering, Electrical Engineering, or Mechatronics - 2 or more years of professional experience in machine vision, computer vision, robotics, or automation - Strong C++ or C# proficiency with working knowledge of Python - Hands-on experience with OpenCV and/or industrial libraries such as Halcon, VisionPro, Matrox, or pylon vTools - Demonstrated ability to build and train machine learning or AI models that have been shipped to production - Working knowledge of at least one GUI framework: Qt/QML, WPF/.NET, or PySide - Proficiency with vendor SDKs in live production applications - Understanding of multithreading, performance profiling, and real-time constraints - Competence with version control (Git), automated testing, and peer code review - Self-directed approach to algorithm development with minimal guidance Bonus skills and experience: - Telecentric or macro optics, line-scan imaging, Scheimpflug principle, modulation transfer function (MTF), lens characterization - Industrial camera interfaces: CoaXPress, 10 GigE, frame grabbers, strobe and lighting controllers - Specialist platforms including Halcon, Cognex, or Keyence - 2D and 3D vision techniques, surface profilometry, or precision metrology - Deep learning applications for defect detection and anomaly identification - DataMatrix or OCR barcode inspection with ISO/IEC 15415 and 15416 quality grading - GPU acceleration frameworks such as CUDA or TensorRT - Industrial protocols: EtherCAT, OPC UA, PROFINET - Statistical quality methods: Gauge R&R, statistical process control (SPC), traceability systems, fault recovery mechanisms