Intern- ADTS PIE RDA

Intern, Realtime Defect Analysis (RDA) Engineering

Location: Singapore

Department: Realtime Defect Analysis (RDA) Engineering

Project Title: Digital Solutions for Artificial Intelligence Project Management and AI Adoption Enablement

Join an inclusive team passionate about using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible, with a commitment to integrity, sustainability, and giving back to our communities.

Project Description

The Realtime Defect Analysis (RDA) function generates significant engineering and manufacturing data used to monitor process health, identify defect trends, and drive yield improvement within a semiconductor manufacturing environment.

As an intern within the RDA Engineering team, you will design and develop AI-enabled digital solutions that improve visibility, governance, and execution of Artificial Intelligence initiatives, while enabling broader adoption of AI technologies across engineering workflows. The project will involve developing project management dashboards, workflow automation capabilities, and AI-powered productivity solutions that transform engineering data into actionable insights.

The intern will gain exposure to semiconductor manufacturing processes, defect analysis methodologies, data analytics, software development, workflow automation, and the practical application of Generative AI, AI assistants, agentic AI, and other AI-enabled technologies in an engineering environment.

Objective of the Project

• Develop scalable digital solutions that improve management and visibility of Artificial Intelligence initiatives within the RDA organization.
• Design automated dashboards and reporting capabilities that provide insights into AI project progress, adoption, and value realization.
• Apply Artificial Intelligence, automation, and data analytics techniques to simplify engineering workflows and reduce repetitive manual activities.
• Evaluate innovative AI-enabled approaches that increase engineering productivity and user engagement.

Project Scope

• Develop visualization dashboards and project management solutions for tracking Artificial Intelligence-related initiatives, milestones, adoption metrics, and outcomes.
• Design and implement AI-enabled applications, workflow automation solutions, or AI assistant capabilities that enhance engineering productivity.
• Analyze engineering processes to identify opportunities where Generative AI, agentic AI, or automation solutions can deliver measurable value.
• Integrate data from multiple engineering sources to provide consolidated views for project monitoring and decision-making.
• Apply software engineering, data analytics, and data visualization techniques to develop maintainable and scalable digital solutions.

Learning Opportunities

• Acquire foundational knowledge of semiconductor manufacturing, wafer fabrication processes, and Realtime Defect Analysis methodologies.
• Develop an understanding of defect analysis, statistical process control, process monitoring, and engineering decision-making workflows.
• Gain hands-on experience in software development, data analytics, automation, dashboard development, and system integration.
• Learn how Artificial Intelligence, Generative AI, AI assistants, large language models, and agentic AI technologies are applied within manufacturing engineering environments.
• Collaborate with multidisciplinary engineering, manufacturing, and software development teams on real-world digital transformation initiatives.

Deliverables

• An AI project management and visualization platform that provides visibility into Artificial Intelligence initiatives and adoption progress.
• AI-enabled applications, automation solutions, or workflow enhancement tools that improve engineering productivity.
• Technical documentation, testing evidence, deployment guidelines, and reusable software components.
• A final technical presentation summarizing project objectives, implementation approaches, key outcomes, and future enhancement opportunities.

Impact of the Project

• Improve visibility and governance of Artificial Intelligence initiatives across the RDA organization.
• Accelerate AI adoption and usage through practical and scalable engineering solutions.
• Enhance engineering productivity by reducing manual effort through automation and AI-enabled workflows.
• Establish reusable digital frameworks that can support future Artificial Intelligence and automation initiatives.

Skillsets Required

• Strong analytical, problem-solving, and critical thinking skills.
• Experience with programming, data analytics, or automation tools such as Python, R, SQL, Power Automate, Power BI, or equivalent technologies.
• Familiarity with software development practices, data visualization, and workflow automation concepts.
• Experience using AI-related technologies such as Microsoft Copilot, Claude, Tabnine, AI assistants, large language models, or other AI-enabled development tools.
• Strong communication and collaboration skills, with the ability to translate technical concepts into practical engineering solutions.

Preferred Skillsets

• Experience with web application development, dashboard development, or full-stack software engineering.
• Experience with data engineering, machine learning, Artificial Intelligence, or workflow automation projects.
• Familiarity with semiconductor manufacturing, engineering analytics, or manufacturing data systems.

Course of Interest

The ideal candidate should be pursuing a degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Analytics, Statistics, Electrical Engineering, Electronic Engineering, or a related engineering or science discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of 5 months from Jan to May 2027.

Opportunities for Full Time Employment

Successful completion of the internship may provide exposure to future graduate employment opportunities, subject to business requirements, position availability, and the applicable selection process.