Nmtronics
Website:
nmtronics.com
Job details:
Designation: Camera Systems Engineer
Job Location: Bengaluru
Experience Required : 2-4 Years
Opening - 1
Job Description :
- Design, deploy, and maintain robust industrial camera and lighting architectures for EMS (Electronics Manufacturing Services) Defect Detection systems.
- Calculate and specify camera & lens requirements, lighting , sensor sizes, field of view, and depth of field to ensure optimal and repeatable image capture on the factory floor.
- Design and implement complex lighting setups to highlight specific manufacturing defects.
- Apply principles of Radiometry, Photometry, and Photogrammetry for precise calibration, accurate 3D measurements, and robust optical inspections.
- Perform camera calibration , stereo vision setups, and depth estimation .
- Apply classical Image Processing and Computer Vision techniques to preprocess images, extract features, and build deterministic algorithms
- Integrate vision hardware with factory workflows, PLCs, and production systems.
- Collaborate with the team to capture, validate, and curate high-quality datasets required for model training.
Technical Skills :
- Solid knowledge of classical Image Processing and Computer Vision techniques .
- Knowledge on Industrial imaging hardware including machine vision cameras , CMOS/CCD sensors, and optical filters.
- Extensive experience with Camera Calibration concepts, lens distortion correction.
- Proficiency in Python ,SQL and Bash .Nice to have C/C++ for hardware control, automated image capture, and script-based testing.
- Strong fundamentals in Deep Learning (Vision Models ),Linear Algebra and 3D Geometry for optics and machine vision.
- Strong analytical and problem-solving skills for troubleshooting complex, real-world optical environments and dynamic ambient lighting conditions.
- Strong grasp of physical optics, Radiometry, Photometry, and Photogrammetry
Nice to have :
- Education : Masters (Preferred) with 1+ years of experience or Bachelors with 2-4 years of experience in CS / EC / EE branches.
- Hands-on experience with ML training pipelines, fine-tuning workflows, or annotation tools (CVAT, Roboflow).
- Experience with Embedded C/C++, Linux, or edge deployment inference targets.
- Familiarity with full-stack integration (React / TypeScript frontend + PostgreSQL / FastAPI backend).
- Good understanding of EMS Manufacturing processes, SMT lines, Defect detection, and Statistical Process Control (SPC).
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