Bachelor's degree in Optical Engineering, Optical Sciences, Photonics, Imaging Science, Applied Physics, or Electrical Engineering with optics emphasis
3+ years of relevant experience
Professional experience in machine vision optical design for defect inspection
Hands-on experience with installation and commissioning of inspection systems
Experience specifying requirements with industrial camera and illumination suppliers
Demonstrated ability to quantify inspection performance metrics
Proficiency in C#, C++, or Python for building vision applications
Responsibilities
Design inspection optics for various defect types, including illumination and camera selection
Install and commission inspection systems on the production line
Lead proof-of-concept evaluations for new inspection capabilities
Own optical specifications for new inspection lines from inception to commissioning
Quantify and track inspection performance metrics in production
Set and maintain detection thresholds in collaboration with engineering teams
Monitor and correct image quality on existing production equipment
Develop vision applications for camera control and image acquisition
Build and maintain on-floor viewer for operators and engineers
Support various inspection processes across the manufacturing line
Benefits
Opportunity to work in a cutting-edge solar manufacturing environment
Collaborative team atmosphere with AI and engineering professionals
Hands-on role with direct impact on production quality
Access to advanced optical design and imaging technologies
Potential for professional growth in a rapidly evolving industry
Full Job Description
Description
Optical Engineer
Title: Optical Engineer
Location: Cartersville, GA (Qcells Cartersville Factory)
Department: Smart Intelligence Team
The Optical Engineer will design, install, and own the optics of every vision inspection across Qcells' solar manufacturing line, spanning ingot, wafer, cell, and module processes at the Cartersville (CTV) and Dalton (DLT) plants. The first assignment is optical design and installation: specifying illumination, lens, and camera for each defect type, building the setup on the line, and proving that it reveals what it is meant to reveal. Detection performance is set by the optics before any algorithm sees the image. The role also builds the software that runs around the optics, including camera control and image acquisition, the interface to the AI inference server, and the on-floor viewer used by operators and engineers. Deep learning detection models are developed by dedicated AI engineers on the same team, so this role owns the optics, the application around them, and the measurement of inspection performance rather than model development.
Responsibilities
Design inspection optics for each defect type, covering illumination (wavelength, angle, uniformity), lens, field of view, resolution, and camera or sensor selection, and finalize installation specifications with mechanical and controls engineering
Install and commission inspection systems on the production line, including mounting, alignment, focus and lighting setup, and acceptance criteria for image quality
Lead proof-of-concept evaluation of new inspection capability, including vendor technical assessment, bench trial design, detection-limit measurement, and production readiness decisions
Own optical specifications for new inspection lines from the ground up, including vendor selection, incoming acceptance testing, and commissioning
Quantify and track inspection performance in production (over-kill rate, miss rate, and detection coverage), and design the evaluation sample set and labels required to measure them, including known-good labels
Set and maintain detection thresholds and judgment criteria together with process and quality engineering
Monitor and correct image quality on equipment already in production: focus and brightness drift, field-of-view alignment, tool-to-tool variation, and line-to-line standardization
Determine root-cause attribution when over-kill or miss rates rise, separating optical, process, and model causes, working with AI, process, and equipment engineering
Develop the vision application that runs around the optics, covering camera control, triggering, image acquisition and preprocessing, and the interface to the AI inference server at line speed
Build and maintain the on-floor viewer used by operators and engineers, covering live inspection images and results, defect review and re-judgment, lookup of past inspections by product or tool, and threshold configuration
Support inspection across EL, front-end and back-end AOI, string and solder joint inspection, final visual inspection, wafer surface and saw-mark inspection, and real-time image metrology on crystal growth, spanning visible, near-infrared, and laser-based measurement
Required Qualifications
Bachelor's degree in Optical Engineering, Optical Sciences, Photonics, Imaging Science, Applied Physics, or Electrical Engineering with an optics or imaging emphasis
3+ years of relevant experience
Professional experience in machine vision optical design, covering selection and validation of illumination, lenses, and cameras for defect inspection
Hands-on experience installing, aligning, and commissioning inspection systems on a production line, and sustaining them afterward
Experience specifying requirements and working directly with industrial camera and illumination suppliers
Demonstrated experience quantifying inspection performance, including over-kill and miss rates, threshold setting, and before-and-after verification of changes
Working proficiency in C#, C++, or Python, sufficient to build and modify vision applications and operator screens
Ability to collaborate effectively with colleagues, customers, suppliers, and stakeholders from different technical backgrounds
Preferred Qualifications
High-volume inspection experience in semiconductor, display, or solar manufacturing
Electroluminescence (EL) inspection experience
3D metrology experience such as laser triangulation, structured light, or confocal measurement
Measurement systems analysis (Gage R&R) or inspection capability studies
Experience with optical design and simulation tools such as Zemax
Hands-on use of machine vision SDKs (Halcon, Cognex VisionPro, OpenCV) and camera interface standards (GigE Vision, USB3 Vision, GenICam)
Experience integrating vision systems with external systems over network protocols (TCP/IP, HTTP/REST, or gRPC)
Experience developing operator-facing GUI applications (WinForms/WPF or Qt)
Experience interfacing vision systems with manufacturing equipment, PLC, or MES
