Internship - Integration of AI into Reliability and Qualification Digital Workflow

Join our Back-End Reliability and Qualification team and gain hands-on experience in integrating AI into engineering workflows. In this internship, you will explore real-world reliability and qualification processes, identify opportunities for AI adoption, and contribute to developing practical solutions that improve efficiency, reduce manual effort, and support systematic implementation across the organization.

Your role Key responsibilities in your new role

- Identify Needs: Map agreed workflows and identify repetitive tasks that are suitable for AI-supported solutions

- Experience Research: Review existing processes to evaluate use cases that deliver cost advantages, time savings, and effective system implementation

- Work Reliably: Prepare approved datasets and documents while ensuring data quality, traceability, and compliance with established standards

- Be Creative: Build and test AI prototypes for selected use cases such as report drafting, information retrieval, or data extraction

- Strength in Numbers: Compare AI-generated outputs against engineer-reviewed examples and record errors, limitations, and performance metrics

- Convince Others with Your Words: Document solutions and demonstrate outcomes to users while following data-access requirements and maintaining human review of engineering decisions Learning Outcomes:

- Business Understanding: Explain Back-End Reliability and Qualification workflows and translate user requirements into practical AI use cases

- Technical Expertise: Develop and connect AI prototypes to approved data sources using traceable datasets

- Knowledge Development: Apply fundamental AI and language-model techniques and understand their limitations in engineering applications

- Problem Solving: Evaluate output quality and workflow efficiency against manual baselines using defined test cases

- Professional Growth: Apply responsible AI practices, including confidentiality requirements and human oversight of generated content

- Communication Skills: Present a working solution and deliver reusable code together with clear user documentation

Your profile Qualifications and skills to help you succeed

- Study Field: Be currently enrolled in a degree program in Computing, Data Science, Engineering, or a related discipline

- Experience: Bring foundational knowledge of AI or machine learning through coursework or student projects

- Work Style: Demonstrate structured problem-solving skills and a careful approach to validating data and results

- Personality: Show strong communication skills, effective documentation practices, and eagerness to learn from engineering professionals

- Skills: Possess basic Python programming skills and experience working with spreadsheet or tabular data; familiarity with language-model prompting, document retrieval, SQL, APIs, Git, or workflow automation tools is an advantage

- Language Skills: Demonstrate good written and verbal communication skills in English

#WeAreIn for driving decarbonization and digitalization. As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener. Are you in? We are on a journey to create the best Infineon for everyone.
We strive to create the best Infineon for everyone by embracing diversity and inclusion. We welcome applicants for who they are and offer a workplace built on trust, openness, respect and equal opportunity.
Our hiring decisions are based on skills and experience. Even if you don’t meet every requirement, we encourage you to apply.
Please let your recruiter know if you need any accommodations during the interview process.
Learn more about our various contact channels and about Diversity & Inclusion at Infineon.

Lau Yu Qin