About the role
AI summarisedThis internship involves developing an AI-driven tool to analyze equipment incident data from the Equipment Tracking Interface (ETI), integrate with Microsoft Teams for validation, and apply machine learning to identify recurring failure patterns using Pareto analysis. The goal is to provide engineering teams with actionable insights to address chronic failures in semiconductor manufacturing environments.
IDMOnsiteFront End
Key Responsibilities
- Develop an AI-driven tool to intelligently dissect incident data into Pareto buckets
- Leverage AI and machine learning to interpret human-written inputs from the Equipment Tracking Interface (ETI)
- Validate incidents via integration with Microsoft Teams
- Analyze historical data to uncover recurring failure patterns
- Provide clear direction for engineering teams to address chronic failures
- Collaborate with engineering teams to refine failure classification and analysis
Requirements
- Currently pursuing a degree in Computer Science, Data Science, Electrical Engineering, or related field
- Experience or coursework in AI, machine learning, or data analysis
- Familiarity with semiconductor manufacturing or equipment tracking systems (e.g., ETI) is a plus
- Proficiency in programming languages such as Python
- Experience with data visualization and analytical tools
- Strong problem-solving skills and ability to work with technical teams
- Excellent communication skills for presenting findings to engineering stakeholders
- Ability to work in a collaborative, fast-paced R&D environment