The Smart Visual Inspection platform enables engineers to create guided inspection procedures, train and deploy AI models, provide immediate pass/fail feedback, and capture inspection results for traceability. The Austin proof of concept will initially focus on pack-out applications such as verifying product accessories, quantities, text, labels, orientation, and packaging contents
Responsibilities
Assist with the development and implementation of Smart Visual Inspection solutions for Order Fulfillment, packaging, and finished-product inspection.
Study current inspection and pack-out processes, identify improvement opportunities, and translate operational requirements into structured inspection workflows.
Work with engineers and production personnel to identify representative products and packaging configurations for proof-of-concept testing.
Capture, organize, and maintain image datasets under representative operating conditions.
Label and annotate images used for computer-vision model training.
Safely move, position, and prepare product cartons and packaging materials while capturing images from multiple angles for computer-vision model development and validation.
Develop and maintain digital inspection procedures and inspection recipes.
Train and test computer-vision models for applications such as
Object presence and absence verification
Quantity verification
Packaging-content validation
Label and text recognition
Product-position and orientation checks
Region-based classification
Evaluate model performance and help adjust confidence thresholds to balance false accepts and false rejects.
Conduct controlled tests using representative products, packaging materials, accessories, labels, and configurations.
Support the setup and optimization of cameras, fixtures, workstations, backgrounds, and diffuse lighting.
Evaluate how camera position, lighting, glare, shadows, object placement, and image quality affect inspection reliability.
Record test results, model performance, inspection exceptions, process times, and identified improvement opportunities.
Assist with root-cause analysis and troubleshooting when an inspection process produces inconsistent or unexpected results.
Develop standard operating procedures, work instructions, training materials, and technical documentation.
Support operator training and collect feedback during pilot deployment.
Collaborate with cross-functional teams to incorporate operational feedback and improve the inspection process.
Help establish a repeatable process for maintaining inspection procedures, trained models, configuration files, and revision history.
Present project status, technical findings, validation results, and final recommendations to engineering and operations stakeholders.
These responsibilities reflect the project’s documented needs around image capture and annotation, model training, validation thresholds, camera and lighting consistency, inspection-workflow development, traceability, and pack-out verification
Qualifications
Required
Currently pursuing a bachelor’s or master’s degree in
Industrial Engineering
Manufacturing Engineering
Mechanical Engineering
Robotics, Automation, or a related technical discipline
Basic understanding of manufacturing, engineering, quality, automation, computer vision, or data-analysis concepts.
Strong analytical and structured problem-solving skills.
Ability to collect, organize, analyze, and clearly present technical data.
Ability to follow defined test methods and accurately document results.
Ability to work effectively in a hands-on manufacturing or operations environment.
Strong written and verbal communication skills.
Ability to collaborate with engineers, operators, quality personnel, and other cross-functional stakeholders.
Proficiency with Microsoft Excel, PowerPoint, and Word.
Willingness to learn new software tools, inspection methods, and manufacturing processes.
Ability to manage assigned tasks with appropriate guidance and communicate progress, risks, and technical issues.
Ability to occasionally lift and move boxes weighing up to 50 pounds, with or without reasonable accommodation, as needed to position products and packaging materials for image capture, model training, and inspection testing.
Preferred Qualifications
Coursework or project experience in one or more of the following
Computer vision
Machine learning
Image processing
Industrial automation
Robotics
Manufacturing systems
Quality engineering
Operations research
Lean manufacturing or Six Sigma
Data analytics
Experience using Python, MATLAB, OpenCV, or another analytical or image-processing tool.
Experience collecting, cleaning, labeling, or analyzing image datasets.
Familiarity with object detection, optical character recognition, classification, or anomaly-detection concepts.
Experience with cameras, lighting, sensors, fixtures, or automated inspection equipment.
Familiarity with process mapping, time studies, root-cause analysis, validation, or statistical analysis.
Experience creating standard operating procedures, work instructions, test reports, or technical presentations.
Interest in smart manufacturing, Industry 4.0, digital work instructions, artificial intelligence, and operations technology.
Previous internship, laboratory, capstone, research, or project experience in a manufacturing or engineering environment.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
Assist with the development and implementation of Smart Visual Inspection solutions for Order Fulfillment, packaging, and finished-product inspection.
Study current inspection and pack-out processes, identify improvement opportunities, and translate operational requirements into structured inspection workflows.
Work with engineers and production personnel to identify representative products and packaging configurations for proof-of-concept testing.
Capture, organize, and maintain image datasets under representative operating conditions.
Label and annotate images used for computer-vision model training.
Safely move, position, and prepare product cartons and packaging materials while capturing images from multiple angles for computer-vision model development and validation.
Develop and maintain digital inspection procedures and inspection recipes.
Train and test computer-vision models for applications such as
Object presence and absence verification
Quantity verification
Packaging-content validation
Label and text recognition
Product-position and orientation checks
Region-based classification
Evaluate model performance and help adjust confidence thresholds to balance false accepts and false rejects.
Conduct controlled tests using representative products, packaging materials, accessories, labels, and configurations.
Support the setup and optimization of cameras, fixtures, workstations, backgrounds, and diffuse lighting.
Evaluate how camera position, lighting, glare, shadows, object placement, and image quality affect inspection reliability.
Record test results, model performance, inspection exceptions, process times, and identified improvement opportunities.
Assist with root-cause analysis and troubleshooting when an inspection process produces inconsistent or unexpected results.
Develop standard operating procedures, work instructions, training materials, and technical documentation.
Support operator training and collect feedback during pilot deployment.
Collaborate with cross-functional teams to incorporate operational feedback and improve the inspection process.
Help establish a repeatable process for maintaining inspection procedures, trained models, configuration files, and revision history.
Present project status, technical findings, validation results, and final recommendations to engineering and operations stakeholders.
These responsibilities reflect the project’s documented needs around image capture and annotation, model training, validation thresholds, camera and lighting consistency, inspection-workflow development, traceability, and pack-out verification
Required
Currently pursuing a bachelor’s or master’s degree in
Industrial Engineering
Manufacturing Engineering
Mechanical Engineering
Robotics, Automation, or a related technical discipline
Basic understanding of manufacturing, engineering, quality, automation, computer vision, or data-analysis concepts.
Strong analytical and structured problem-solving skills.
Ability to collect, organize, analyze, and clearly present technical data.
Ability to follow defined test methods and accurately document results.
Ability to work effectively in a hands-on manufacturing or operations environment.
Strong written and verbal communication skills.
Ability to collaborate with engineers, operators, quality personnel, and other cross-functional stakeholders.
Proficiency with Microsoft Excel, PowerPoint, and Word.
Willingness to learn new software tools, inspection methods, and manufacturing processes.
Ability to manage assigned tasks with appropriate guidance and communicate progress, risks, and technical issues.
Ability to occasionally lift and move boxes weighing up to 50 pounds, with or without reasonable accommodation, as needed to position products and packaging materials for image capture, model training, and inspection testing.
Preferred Qualifications
Coursework or project experience in one or more of the following
Computer vision
Machine learning
Image processing
Industrial automation
Robotics
Manufacturing systems
Quality engineering
Operations research
Lean manufacturing or Six Sigma
Data analytics
Experience using Python, MATLAB, OpenCV, or another analytical or image-processing tool.
Experience collecting, cleaning, labeling, or analyzing image datasets.
Familiarity with object detection, optical character recognition, classification, or anomaly-detection concepts.
Experience with cameras, lighting, sensors, fixtures, or automated inspection equipment.
Familiarity with process mapping, time studies, root-cause analysis, validation, or statistical analysis.
Experience creating standard operating procedures, work instructions, test reports, or technical presentations.
Interest in smart manufacturing, Industry 4.0, digital work instructions, artificial intelligence, and operations technology.
Previous internship, laboratory, capstone, research, or project experience in a manufacturing or engineering environment.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
