Automated Defect Classification 2.0 Engage with Multiple Teams and Departments : Collaborate with various teams, including Engineering, IT, QA, and SMAI, to gather diverse expertise and insights for model training. Use RDAViewer for Data Verification : Apply RDAViewer to verify the accuracy of defect data and ensure the integrity of the training dataset. Data Collection and Analysis for Qualification : Collect and analyze defect data to qualify the ADC models, ensuring they meet the required performance standards. Model Optimization : Continuously refine and optimize the ADC models based on feedback and performance metrics. Cross-Platform Integration : Ensure seamless integration of ADC models across ATI Wind, Dragonfly, and Sam Scan platforms. User Training : Provide training sessions for team members on how to use and interpret the ADC models. Documentation : Maintain comprehensive documentation of the model training process, data verification, and analysis procedures. Performance Reports : Generate detailed performance reports for each model, highlighting accuracy, precision, recall, and other relevant metrics. Currently pursuing a degree in Metrology, Engineering, Materials Science, or a related field. Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights. Excellent written and verbal communication skills to effectively collaborate with cross-functional teams and document processes. Ability to work collaboratively in a team environment and contribute to the success of the project.
