全职 AI Application Engineer 工作, 薪水, VisionPower Semiconductor Manufacturing Company (VSMC) East Region (Singapore) 公司招聘中 - Ricebowl

Role Summary

We are looking for a highly skilled and motivated AI Application Engineer to apply modern Artificial Intelligence technologies, particularly Large Language Models (LLMs), Generative AI, and AI-powered applications, to advanced 300mm semiconductor wafer-fab manufacturing.

The successful candidate will work closely with Fab users, manufacturing and engineering teams, solution architects, and IT teams to identify opportunities where AI can improve manufacturing operations, engineering productivity, knowledge management, troubleshooting, and decision-making.

The role covers the full lifecycle of AI application development—from understanding user requirements and designing solutions, to development, deployment in the production Fab, performance evaluation, and continuous improvement based on real-world results and user feedback.

Key Responsibilities

• Work closely with Fab users, engineers, and stakeholders to understand manufacturing and engineering requirements, operational challenges, and opportunities for AI application.
• Identify and define practical AI/LLM use cases for 300mm semiconductor wafer-fab operations and engineering.
• Translate user requirements and business problems into technical requirements and AI application solutions.
• Design and develop AI-powered applications in collaboration with solution architects and cross-functional engineering teams.
• Apply modern AI technologies, including LLMs, Generative AI, Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, and machine learning, where appropriate.
• Develop solutions that leverage manufacturing and engineering data, knowledge bases, documents, reports, and relevant Fab systems.
• Integrate AI applications with existing manufacturing and enterprise systems, databases, APIs, and workflows.
• Work with relevant teams to deploy AI solutions into the production Fab environment.
• Monitor application performance, reliability, usability, and AI response quality after deployment.
• Evaluate and continuously improve the accuracy and effectiveness of AI solutions based on user feedback, production results, and engineering requirements.
• Collaborate with process engineers, equipment engineers, manufacturing teams, IT teams, and other stakeholders to drive the adoption of AI solutions.
• Ensure AI applications are designed with appropriate considerations for data security, reliability, scalability, and maintainability.
• Keep up to date with emerging AI technologies and evaluate their potential applications in semiconductor manufacturing.

Requirements

• PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field
• Strong understanding of modern AI/ML technologies, particularly Large Language Models (LLMs) and Generative AI
• Hands-on experience developing AI/ML or software applications involving AI technologies
• Strong programming and software development skills, preferably with Python
• Strong analytical and problem-solving abilities, with the ability to understand complex problems and develop practical solutions
• Ability to translate user requirements and manufacturing challenges into effective technical solutions
• Effective communication and teamwork skills, with the ability to collaborate with both technical and non-technical stakeholders
• Candidates with the following experiences preferred
• Experience in the semiconductor industry, wafer Fab, or high-volume manufacturing environment
• Possess knowledge of 300mm semiconductor wafer-fab manufacturing processes and Fab operations
• Familiarity with semiconductor manufacturing systems and data, such as MES, equipment data, process data, SPC, FDC, APC, yield, and engineering systems
• Experience in process engineering, equipment engineering, manufacturing engineering, yield engineering, or related semiconductor engineering functions
• Experience developing applications using LLMs, RAG, vector databases, prompt engineering, AI agents, or LLM evaluation
• Experience deploying AI/ML applications into production environments
• Experience with APIs, databases, cloud platforms, containers, or microservices
• Experience working with large-scale manufacturing data or engineering knowledge bases