AI Application Engineer

Role Overview

We seek an accomplished and driven AI Application Engineer to implement cutting-edge Artificial Intelligence technologies—including Large Language Models (LLMs), Generative AI, and AI-enhanced applications—in advanced 300mm semiconductor wafer fabrication manufacturing. The role entails close collaboration with fabrication users, engineering teams, solution architects, and IT professionals to discover where AI can enhance manufacturing processes, engineering efficiency, knowledge handling, problem solving, and decision-making.

Key Responsibilities

• Engage with fab stakeholders and engineers to comprehend manufacturing and engineering needs, operational challenges, and AI application potential.
• Pinpoint and define viable AI/LLM use cases tailored to 300mm semiconductor wafer fabrication operations and engineering.
• Convert user and business requirements into clear technical specifications and AI solution designs.
• Collaborate with solution architects and engineering groups to design and build AI-driven applications.
• Utilize contemporary AI technologies including LLMs, Generative AI, Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, and machine learning as suitable.
• Create solutions integrating manufacturing data, knowledge repositories, documentation, reports, and relevant fab systems.
• Incorporate AI applications with existing manufacturing and enterprise systems, databases, APIs, and operational workflows.
• Coordinate with teams to deploy AI solutions into active production fab environments.
• Observe and analyze application performance, reliability, user experience, and AI response quality post-deployment.
• Continuously assess and enhance AI solution accuracy and functionality based on user input, production outcomes, and engineering feedback.
• Work jointly with process, equipment, manufacturing, and IT engineers as well as other stakeholders to facilitate AI adoption.
• Ensure AI systems are architected with stringent data security, scalability, reliability, and ease of maintenance.
• Stay informed of emerging AI innovations and assess their relevance for semiconductor manufacturing applications.

Candidate Requirements

• Doctorate degree in Computer Science, AI, Machine Learning, Data Science, or closely related technical discipline.
• Deep knowledge of modern AI/ML techniques, especially Large Language Models and Generative AI.
• Practical experience in developing AI/ML or software applications involving AI technology.
• Strong programming skills, preferably in Python.
• Excellent problem-solving and analytical abilities to tackle complex challenges and engineer effective solutions.
• Capability to translate manufacturing user needs into technical requirements.
• Strong communication and collaborative skills to work effectively across technical and non-technical teams.
• Preferred qualifications include experience in the semiconductor sector, wafer fable environments, or large-scale manufacturing.
• Familiarity with 300mm wafer-fab processes and operations.
• Knowledge of semiconductor manufacturing systems and data types (MES, equipment and process data, SPC, FDC, APC, yield and engineering systems).
• Experience in semiconductor engineering disciplines such as process, equipment, manufacturing, or yield engineering.
• Expertise with LLMs, RAG, vector databases, prompt design, AI agents, or LLM evaluation.
• Experience deploying AI/ML applications to production environments.
• Experience with APIs, databases, cloud technologies, containerization, or microservices architectures.
• Experience handling large-scale manufacturing data or engineering knowledge bases.