Fixing Mistakes: Issuing Non-Conformance Reports (NCR) when work is sub-standard, and tracking them to make sure the contractor fixes the issue properly.
Testing Witness: Witnessing and signing off on factory tests (FAT) and site testing/commissioning (T&C) for critical M&E systems.
Education: Degree in Electrical or Mechanical Engineering (registered with BEM).
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Document routine preventive maintenance and unscheduled failures details on system database
Provide inputs to Shift Coordinator or Equipment Engineer to improve PM cycle-time, tool availability, quality/workmanship, reduce media scrap and cost of ownership.
Provide Technical training and certification for junior technician.
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Utilizes appropriate tools and equipment to perform necessary design work including design creation, design analysis, and design verification.
Produces comprehensive project documentation based on the needs of the project and in accordance with the quality and change management procedures and guidelines.
Bachelor’s Degree required with 1 or more years of related experience preferred.
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Stakeholder Alignment: Act as the primary technical liaison between internal stakeholders, global manufacturing sites, and outsourced engineering partners.
Experience: 5+ years of dedicated Project Management experience specifically within the semiconductor capital equipment industry.
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Develop and present test plans when problems arise, coordinate testing and data acquisition
Candidates must possess a recognized Degree in Engineering, Electrical/ Electronics/ Communication Engineering or equivalent with minimum 1 year working experience.
Possess analytical/ problem solving skills, data acquisition skills, and ability to use statistical tools and techniques such as CP & CPK study.
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3) Setup various test stations, workstations, machines, tools and equipment in production lines for supporting new product introduction, capacity increase, productivity improvement and other business needs.
Evaluate, fine-tune, and improve AI systems through structured testing, quality measurement, safety guardrails, and hallucination reduction techniques.
Design and implementation of machine learning models in different domains (e.g. SCM, Manufacturing, Product Management and Corporate Functions) following the CRISP- DM process.
Train, fine-tune, and optimize deep learning models for various applications.
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