Job Description • Engineer and deploy deep learning models, specifically utilizing Convolutional Neural Networks (CNNs) and Segment Anything Models (SAM), to automate the classification and grading of display image quality and defects. • Design and implement automated pipelines for large-scale dataset from existing testers, preparation, and analysis to validate image scoring algorithms against real-world hardware performance. • Develop signal processing and computer vision algorithms to perform object detection and segmentation on display outputs, converting subjective visual criteria into objective engineering metrics. • Design and simulate optical systems involving geometric optics, wave optics, and Fourier optics, ensuring alignment between theoretical models and hardware implementation We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Ph.D. or Master’s degree in Electrical Engineering, Electro-Optics, Computer Science, or a related field. • Proficiency in programming and software development using Python/PyTorch and MATLAB for algorithm implementation and hardware control. • Hands-on project experience in Computer Vision and Deep Learning, with specific expertise in image segmentation, object detection, and classification using architectures like CNNs and SAM. • Experience in building and validating predictive models using large-scale datasets for image analysis tasks. • Strong fundamental knowledge of optics, including Fourier analysis and digital filters, applied to imaging and display systems. • Good communication skills to work in a cross functional setting.