Machine Vision Engineer

Machine Vision Engineer

Date: Jun 2, 2026

Location: Painted Post, NY, US, 14870 Hickory, NC, US, 28601 Fairport, NY, US, 14450 Charlotte, NC, US, 28216

Company: Corning

Requisition Number: 75407

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.

• 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 Vision Pro, 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, Ether Net/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.

• 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, Ether Net/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.

• 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 Tensor Flow / 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…