Machine Vision Engineer

CorningVillage of Fairport, NY
Onsite

About The Position

Corning is seeking an experienced Machine Vision Engineer to develop and deploy machine vision and PC-based control solutions that enable real-time quality assurance and closed-loop control in automated manufacturing systems. This role encompasses automated optical inspection (AOI), image processing, defect detection, and vision-guided automation — with a strong emphasis on designing solutions that are scalable, repeatable, and production-ready across multiple manufacturing environments. The successful candidate will play a critical role in advancing Corning's smart manufacturing and Industry 4.0 capabilities.

Requirements

  • Demonstrated hands-on experience with machine vision platforms — including Cognex, Keyence, HALCON, NI Vision, MVTec MERLIC, or equivalent — with a track record of deploying systems into production manufacturing environments.
  • Proficiency in PC-based control programming using Python, C++, C#, or LabVIEW; experience with Beckhoff TwinCAT, soft PLC, or NI real-time systems is highly valued.
  • Track record of transitioning automated inspection, AOI, or machine vision technologies from R&D into sustained production use.
  • Ability to integrate vision inspection outputs with PLC, SCADA, HMI, and MES systems via OPC-UA, EtherNet/IP, or GigE Vision standards.
  • Proven ability to build scalable automation solutions for multi-site manufacturing deployment; strong documentation, communication, and cross-functional collaboration skills.
  • Willingness to travel up to 50% in a project-based role supporting multiple Corning manufacturing sites, including travel for equipment builds, commissioning, and ramp-up; offers exposure to global, cutting-edge advanced manufacturing and automation solutions. Travel level varies by project phase and milestone.

Nice To Haves

  • Bachelor's degree (or higher) in Electrical Engineering, Computer Engineering, Mechanical Engineering, Optical Engineering, Mechatronics, Computer Science, or closely related discipline.
  • 5+ years in machine vision, controls engineering, or industrial automation
  • Familiarity with camera selection, lighting design, lens selection, and sensor calibration for industrial environments.
  • Experience with deep learning vision tools such as Cognex ViDi, MVTec MERLIC, Azure Custom Vision, or TensorFlow / PyTorch applied to industrial inspection.
  • Knowledge of USB3 Vision, CoaXPress, or Camera Link standards; experience with 3D vision or structured light systems a plus.
  • Background in robotics, motion control, or vision-guided robotics; experience in glass, fiber optics, semiconductor, or precision manufacturing preferred.

Responsibilities

  • Design and implement machine vision systems for in-process inspection — including defect detection, dimensional gauging, pattern recognition, surface inspection, barcode verification, and optical character recognition (OCR) — across automated production equipment.
  • Select, configure, and deploy vision hardware including cameras, lighting systems, lenses, and frame grabbers; develop vision algorithms using Cognex VisionPro, Keyence, HALCON / MVTec, OpenCV, or NI Vision using Python, C++, C#, or LabVIEW.
  • Integrate vision inspection solutions with PC-based control and automation platforms; interface with PLC, SCADA, HMI, and MES systems via OPC-UA, EtherNet/IP, or GigE Vision protocols.
  • Partner with mechanical, process, and systems engineers to align automated inspection and closed-loop control solutions with production quality requirements; translate manufacturing process knowledge into robust vision system specifications.
  • Support commissioning, tuning, and long-term optimization of vision systems and motion control solutions; perform camera calibration, lighting optimization, and algorithm tuning to achieve target inspection performance.
  • Architect repeatable, scalable automated inspection solutions designed for deployment across multiple manufacturing facilities; document systems to support long-term maintainability and knowledge transfer.

Benefits

  • The range for this position is - assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.
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