Senior Engineer – Machine Vision & Automated Inspection

Greene Tweed•Kulpsville, PA

About The Position

At Greene, Tweed, you'll find the cutting-edge technology, world-class polymer expertise and endless advancement opportunities you'd expect from a multi-national industry leader. You'll find them all in an environment that embraces diversity in people and opinions, moves decision making to the point of impact, and celebrates your success. If you enjoy continuous learning and are excited about working with and creating technological solutions, explore career opportunities with Greene, Tweed.

Requirements

B.S. degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, or a related engineering discipline.
A3 Certified Vision Professional (CVP-Basic or CVP-Advanced), or similar professional certification.
10+ years of experience developing and deploying industrial machine vision systems, preferably in automated inspection applications.
Strong understanding of machine vision fundamentals.
Ability to select cameras, lenses, lighting, and other optical components based on application requirements.
Ability to read and understand electrical, mechanical, and system-level documentation.
Demonstrated experience with multiple machine vision platforms and technologies.
Experience with Cognex and/or Keyence smart-camera systems and their associated software platforms.
Experience with GigE Vision cameras and associated image acquisition software/hardware.
Experience with deep learning for machine vision, including platforms such as Cognex Vision Pro Deep Learning, YOLO, or comparable object-detection/classification frameworks.
Experience with industrial GigE cameras from manufacturers such as Basler, FLIR, Allied Vision, IDS, or similar.
Experience with GenICam / GenTL and camera configuration.
Strong programming or scripting skills and the ability to work with vision-system APIs and software development environments.
Experience with image-processing libraries and programming environments such as C# & Python.
Experience with industrial communications protocols such as EtherNet/IP, PROFINET, TCP/IP, OPC UA, or similar.
Experience with robotic vision applications.
Experience with precision measurement and dimensional inspection.
Experience with multi-camera inspection systems.
Experience with statistical analysis, GR&R, process capability, and inspection-system validation.
Experience working within regulated or highly controlled manufacturing environments.
Hands-on and comfortable working directly with equipment.
Strong troubleshooting and analytical skills.
Comfortable learning new technologies and working across multiple vendor platforms.
Detail-oriented, particularly when developing systems where small changes can significantly affect inspection performance.
Effective communication and interpersonal skills to collaborate with cross-functional teams and stakeholders.
Able to communicate complex technical concepts clearly to both technical and non-technical audiences.
Ability to manage multiple projects simultaneously and meet deadlines in a fast-paced environment.
Willingness and ability to mentor and provide technical guidance to other engineers and technicians.
Ability to travel (domestic & international) up to 5%, varying depending on demand.
This position requires U.S. Person status as defined by applicable law for authorized access to data controlled under the International Traffic in Arms Regulations (ITAR). A U.S. Person includes U.S. Citizens, U.S. Nationals, lawful permanent residents, and workers granted refugee or asylum status in the United States.

Responsibilities

Lead the design, development, integration, and deployment of machine vision systems for manufacturing and production applications.
Determine appropriate camera, lens, lighting, optics, image acquisition, processing, and system architecture for each application.
Program and configure smart camera systems, including Cognex, Keyence and other industrial smart-camera platforms.
Design and implement systems using GigE Vision cameras.
Evaluate and apply traditional rules-based machine vision techniques as well as modern deep-learning-based vision approaches where appropriate.
Develop inspection algorithms for applications including (but not limited to): Defect detection, OCR/OCV, Presence/absence verification, Dimensional & Surface inspection, Pattern and feature recognition.
Develop, train, evaluate, and deploy machine-learning/deep-learning models for challenging inspection applications when conventional vision techniques are insufficient.
Integrate vision systems with PLCs, robots, motion systems, databases, MES systems, and other factory automation equipment.
Perform system debugging, image analysis, root-cause analysis, and optimization of existing inspection systems.
Establish and validate inspection performance, including false-positive/false-negative analysis, repeatability, reproducibility, and capability.
Develop documentation including system specifications, software documentation, inspection standards, validation procedures, and operator instructions.
Support equipment commissioning, production launch, and troubleshooting at manufacturing facilities.
Serve as a technical resource for machine vision technology, application development, and inspection-system design.