Process Control System Engineer

SILTRONIC SILICON WAFER PTE. LTD.

Job Responsibilities

  • Proactively identifies and executes opportunities to enhance wafering performance, improve productivity, and reduce manufacturing cost through advanced algorithms, data‑driven methods, and AI/ML‑enabled solutions.

  • Integrates data‑collection plans and Run‑to‑Run (R2R) control workflows via the Equipment Engineering System (EES) to enable advanced process control and improve process reliability.

  • Translates manufacturing requirements, process behavior, and engineering insights into scalable workflow architectures using Python, SQL‑based databases, containerized services, and internal development frameworks to support high‑volume fab operations.

  • Builds, deploys, and sustains AI/ML models within the manufacturing environment to support diverse AI use cases across the company.

  • Implements DevOps practices and CI/CD pipelines to ensure reliable deployment, version control, and long‑term maintainability of production‑critical software systems.

  • Develops, maintains, and enhances critical workflows and operational dashboards to improve visibility and support data‑driven decision‑making across the manufacturing line.

  • Collaborates closely with Process Engineering, IT Infrastructure, cross‑functional teams, and global technology counterparts to ensure alignment, scalability, and successful cross‑site solution integration.

  • Ensures relevant documentation is observed, updated, and maintained; summarizes activities in monthly reports and submits to Supervisor

  • Strong programming proficiency in Python.

  • Competent in SQL‑based databases for querying and managing structured data.

  • Understanding of manufacturing processes, engineering principles, or process control concepts, with the ability to translate them into workflow or automation solutions.

  • Exposure to DevOps practices, including CI/CD pipelines, version control (Git), automated testing, and production software maintenance is an advantage.

  • Strong analytical thinking with the ability to interpret complex manufacturing data and derive actionable insights.

  • Able to work independently while being an effective team player.

  • Systematic problem‑solving ability and good communication skills.