Camera Systems Engineer

Designation: Camera Systems Engineer

Job Location: Bengaluru

Experience Required : 2-4 Years

Opening - 1

Job Description :

1. Design, deploy, and maintain robust industrial camera and lighting architectures for EMS (Electronics Manufacturing Services) Defect Detection systems.
2. 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.
3. Design and implement complex lighting setups to highlight specific manufacturing defects.
4. Apply principles of Radiometry, Photometry, and Photogrammetry for precise calibration, accurate 3D measurements, and robust optical inspections.
5. Perform camera calibration , stereo vision setups, and depth estimation .
6. Apply classical Image Processing and Computer Vision techniques to preprocess images, extract features, and build deterministic algorithms
7. Integrate vision hardware with factory workflows, PLCs, and production systems.
8. Collaborate with the team to capture, validate, and curate high-quality datasets required for model training.

Technical Skills :

1. Solid knowledge of classical Image Processing and Computer Vision techniques .
2. Knowledge on Industrial imaging hardware including machine vision cameras , CMOS/CCD sensors, and optical filters.
3. Extensive experience with Camera Calibration concepts, lens distortion correction.
4. Proficiency in Python ,SQL and Bash .Nice to have C/C++ for hardware control, automated image capture, and script-based testing.
5. Strong fundamentals in Deep Learning (Vision Models ),Linear Algebra and 3D Geometry for optics and machine vision.
6. Strong analytical and problem-solving skills for troubleshooting complex, real-world optical environments and dynamic ambient lighting conditions.
7. 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).