Kohler Intern - UIRP - Automated Inspection Systems Engineer
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Location: Onsite - Champaign, IL Current enrollment at University of Illinois Urbana Champaign requiredOpportunityThe Automated Inspection Systems Engineer will work on the development and implementation of automated inspection systems across Kohler's manufacturing processes. This individual will address the challenges posed by manual inspection processes, inconsistent results, and the need for improved defect tracking and classification. This role focuses on improving defect detection, standardizing classification, and enhancing process efficiency by using AI-based vision systems. The engineer will collaborate with cross-functional teams to meet Kohler’s high-quality standards and optimize inspection workflows.Responsibilities: Develop Automated Inspection Systems: Design, develop, and deploy automated inspection systems that leverage vision-based machine learning algorithms to enhance speed, accuracy, and consistency compared to manual inspections. 2. Consolidate Defect Library: Create a consolidated defect library across Kohler's Kitchen & Bath (K&B) processes to standardize defect classification and improve data tracking.Improve Consistency and Efficiency: Implement systems to improve the consistency of inspection processes and reallocate inspection personnel to value-added activities.Sensor Integration and Optimization: Work on developing a flexible AI-based vision inspection framework capable of combining inputs from various sensor types and running inference on edge devices to process and classify all defects within Kohler’s manufacturing process requirements.SOP Development: Develop standard operating procedures (SOPs) for adding and teaching new products into the automated inspection systems.Validation and Testing: Validate and test the automated inspection systems to ensure they meet or exceed required cycle times and can detect all defects for a given product category.Preferred Skills and QualificationsCurrent enrollment in Computer Science, Mechanical Engineering, Electrical Engineering, or related field. Master’s degree preferred.Experience in developing automated inspection systems and integrating machine learning algorithms.Proficiency in sensor integration and optimization.Strong project management skills with the ability to meet tight deadlines.Knowledge of industrial manufacturing processes and quality assurance standards.Familiarity with AI/ML technologies and their application in industrial settings.Excellent communication and collaboration skills to work effectively with cross-functional teams.Tech Stack Languages/Frameworks: Python, C++, OpenCV, PyTorch, HuggingFace librariesMachine Learning: Computer Vision algorithmsEdge Computing: NVIDIA Jetson and Vision sensorsMLOps (Cloud): Microsoft Azure, DockerIndustrial Automation: Sensor integration, vision/audio systems


The specific hourly rate offered to a candidate may be influenced by a variety of factors including candidate's education and work location.
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