Machine Vision Engineer
3 days ago
Role Overview
We design, manufacture and deliver high-speed optical sorting, inspection, automatic counting and packaging machines. We are hiring a Machine Vision Engineer proficient in both classical vision and modern deep learning to tackle real-world challenges in surface/cosmetic defect detection, thread inspection, dimensional measurement and high-speed counting.
Key Responsibilities
- Develop & deploy deep learning models (YOLO, CNNs, segmentation, anomaly detection) using TensorFlow/PyTorch for surface & cosmetic defects
- Build classical vision pipelines (OpenCV/HALCON) for dimensional measurement, thread verification and high-speed inspection
- Optimize & deploy models (ONNX, TensorRT, OpenVINO) on industrial PCs/edge devices for 200 to 600 parts/min real-time performance
- Select cameras, lenses, lighting; integrate with PLCs and handle on-site commissioning
Must-Have Skills
- 2+ years deploying DL models (TensorFlow/PyTorch) for industrial defect detection (scratches, dents, cracks, cosmetic flaws)
- Live projects with YOLO (v5/v8/v10), ResNet, EfficientNet, U-Net, etc. in production
- Strong model optimization & deployment experience (ONNX, TensorRT, OpenVINO)
- Solid C++/Python and OpenCV for classical vision
- Camera interfacing (GigE/USB3/CoaXPress), lighting design, PLC integration (OPC-UA, Modbus, EtherCAT, digital I/O)
- Deployed 24 x 7 production-grade vision systems
Why Join Us
End-to-end ownership of real vision systems, hands-on impact on factory floors, deep learning on high-speed lines, and solve tough industrial automation challenges with real factory impact.
Interview Process
- Quick telephonic round
- In-person programming test (Deep Learning + Classical Vision assignment, 2 to 3 hours)
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