About the role
AI summarisedSenior IoT engineer in Singapore designing and deploying Industrial IoT and machine-vision solutions for advanced semiconductor packaging development. Role spans proof-of-concept through factory deployment, focusing on sensing, edge compute, data pipelines, and actionable insights to improve quality and productivity.
IDMOnsiteHIG
Key Responsibilities
- Develop and deploy IIoT solutions end-to-end: sensing strategy, edge compute, connectivity, data ingestion/storage, monitoring, and sustainment (including data quality and traceability)
- Build machine vision solutions: support hardware selection (cameras/optics/lighting), image acquisition strategy, algorithm development, performance validation, and deployment readiness
- Work with process, equipment, automation, quality, and IT/data platform team members to translate manufacturing problems into measurable signals and integrated factory solutions
- Implement principled engineering practices: requirements gather, design reviews, coding standards, testing, documentation, change control, and cybersecurity considerations
- Solve issues in lab and factory environments; perform root-cause analysis, implement corrective actions, and improve system reliability and observability
- Contribute to technical planning and delivery: provide effort estimates, handle tasks, communicate status/risks, and support safe execution and timely closure of actions
Requirements
- Bachelor’s degree (or higher) in Electrical/ Electronics Engineering, Computer Engineering, Computer Science, Mechatronics, or related discipline; or equivalent practical experience
- Hands-on experience delivering IoT/ IIoT , automation, or machine vision solutions in industrial environments, with exposure to system integration and troubleshooting
- Solid understanding of IoT architectures, including edge computing, connectivity, data ingestion, and device/data security fundamentals
- Proficiency in Python and familiarity with software engineering practices (code reviews, testing, CI/CD, and documentation)
- Strong analytical/problem-solving skills and clear communication in a cross-cultural environment
- Willingness to work in lab/factory settings and follow safety, change-control, and operational procedures
- Machine vision hardware/software experience (camera selection, lenses, lighting, calibration) and algorithm development (OpenCV or similar)
- Experience translating manufacturing/tool constraints into measurable signals and sensing strategies (e.g., camera, vibration, ESD/charge, IMU) to detect abnormal conditions and risk
- Data engineering fundamentals: building reliable pipelines, data quality checks, traceability, monitoring/alerting, and scalable data access patterns