Internship - Data and AI (Artificial Intelligence) Analyst
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Quick Summary
Key Responsibilities
Collaborate with experienced Engineer, Biz Process Owners, Biz Subject Matter Experts, Data & AI Engineers at IT (Information Technology).
Requirements Summary
Pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field. Programming & Problem-Solving: Strong problem-solving,
Technical Tools
Other
As part of the ATV OM Customer Quality domain, the intern will contribute to harnessing Automation, Workflows, Data Analytics, and AI to enable Operational Excellence and accelerated digital transformation. The role offers hands-on exposure to the design, Architecture, Development, and deployment of data-driven solutions that create measurable business impact. Your role Key responsibilities in your new role Cross-Functional Collaboration: Collaborate with experienced Engineer, Biz Process Owners, Biz Subject Matter Experts, Data & AI Engineers at IT (Information Technology). Business Problem Solving: Analyze & prioritise Biz problems statements and innovate opportunities to sync with ROI & Implementation complexities. Data Analysis & Visualization: Apply statistical analysis, machine learning, and data visualization techniques to uncover insights from large and complex datasets. Solution Design & Deployment: Design, develop, and deploy production-ready AI & analytics solutions following industry best practices. AI-Enabled Application Development: Build and maintain software applications that integrate AI & machine learning capabilities into business processes. Scalable System Engineering: Contribute to scalable, efficient, and real-time AI systems while ensuring high standards of data quality and engineering excellence. Solution Operations & Support: Support solution operations through troubleshooting, debugging, enhancement requests, and continuous improvement activities. Data Pipeline Development: Develop data pipelines and frameworks to ingest, process, and manage data from diverse enterprise sources. Internship Learning Outcome: Industry Exposure: Gain valuable industry experience and insights into real-world business and technology challenges within the semiconductor sector. Domain Knowledge Development: Develop a foundational understanding of semiconductor Quality Management & Customer complaint management processes through structured onboarding and self-directed learning. Cutting-Edge Technology Experience: Acquire practical experience with cutting-edge technologies, including Generative AI, Computer Vision, Natural Language Processing, and Data Analytics. Enterprise AI Lifecycle Understanding: Learn how enterprise AI solutions are designed, developed, deployed, and managed in production environments. Analytics & Development Proficiency: Build proficiency in analytics platforms, software development practices, and production-grade data science workflows. Professional Skills Enhancement: Strengthen your problem-solving, analytical thinking, and technical communication skills while working on impactful projects. Your profile Qualifications and skills to help you succeed Educational Background: Pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field. Programming & Problem-Solving: Strong problem-solving, critical-thinking, and communication skills, with a passion for building production-grade digital solutions. Software Engineering Foundation: Strong programming skills in Python and a solid foundation in software engineering principles. GenAI & Agentic AI Experience: Hands-on experience with Data pre-processing and analytics, advanced visualization, Generative AI, Large Language Models (LLMs), Agentic AI, RAG, and AI application development. AI Frameworks Proficiency: Familiarity with AI frameworks and tools such as PyTorch, TensorFlow, LangChain, LangGraph, or similar technologies. AI Architecture Knowledge: Understanding of prompt engineering, AI agent orchestration, vector databases, embeddings, and knowledge retrieval systems. Cloud & DevOps Exposure: Exposure to REST APIs, cloud platforms (AWS/Azure/GCP), containers (Docker/OpenShift), and modern application development practices. #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
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Where is the job
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About this job
- Posted
- Today
Listing Details
- Posted
- October 19, 2026
- First seen
- October 19, 2026
- Last seen
- October 19, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 56%
- Scored at
- October 19, 2026
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