Software Engineer

Responsibilities

• Design, select and implement electrical and control hardware for new, modified, or upgraded production machines.

• Prepare and review system specifications, requirements, drawings, control panels, functional descriptions, and Single Line Diagrams (SLD).

• Develop, debug, and troubleshoot PLC programs for new and existing equipment.

• Develop simple PC-based software for machine control, data logging, device communication, and automation support.

• Integrate machine data with basic data analysis or machine learning models (e.g. classification, prediction, anomaly detection) for process improvement and monitoring.

• Coordinate with Equipment Engineering (EQE) and Design Engineers on equipment and process improvements.

• Support EQE and Facilities Technicians in troubleshooting machine and system issues.

• Participate in machine commissioning, testing, and on-site support when required.

• Document software, control logic, and system changes clearly for maintenance and knowledge transfer.

Requirements

• Diploma or Degree in Electrical Engineering, Computer Science, Automation, Mechatronics, or equivalent.

• Relevant hands-on experience in PLC programming and machine automation will be considered in lieu of formal qualifications.

• Minimum 2 years of relevant working experience in automation, machine control, or equipment software.

• Hands-on experience in machine building or fast‑paced equipment projects.

• Strong knowledge of electrical schematics, control circuits, motor controls, and materials take‑off.

• Proficiency in PLC/HMI programming, including but not limited to:

  • Keyence

  • Omron

  • Allen Bradley

  • Mitsubishi

• Experience with PC software development is an advantage, such as:

  • C#, Python, or similar languages

  • Basic UI development and equipment communication (e.g. TCP/IP, serial, vision systems)

• Basic understanding of AI / machine learning concepts (e.g. data preparation, simple models using Python libraries).

• Proficient in MS Office.

• Strong troubleshooting and problem‑solving skills.

• Good communication skills (verbal and written).

• Ability to manage multiple tasks and work independently with minimal supervision.

• Exposure to applying machine learning to equipment data, vision systems, or process optimization is an advantage.

• Familiarity with industrial vision systems or data acquisition.