INSP Process Engineer

Role Purpose

• To support flexible production modes and ongoing project growth at our High Flexibility Plant, sufficient packing engineering resources are essential. We are seeking a new Packing Process Engineer to strengthen the team and ensure robust technical coverage of the packing lines.
• This role seeks an equipment-experienced and digitally fluent engineer to support the Packing Process function. The engineer is accountable for the technical performance, quality outcomes, equipment reliability, and continuous improvement of our packing lines, with a strong focus on mechanical equipment, automation, and process optimization.

Key Responsibilities

[Packing process ownership]:

• Establishes the Packing operation process and sustains daily performance; troubleshoots production upsets and equipment downtime on the packing lines. Supports packing equipment and control system improvements and develops the most efficient packing technology. Designs, modifies, and recommends equipment (conveyors, robots/manipulators, servo-driven mechanisms, guide rails, etc.) to meet or exceed operational requirements.
• Lead MEE / DMAIC root-cause investigations for systemic Packing issues; drive containment, fundamental understanding, and permanent corrective actions.
• Define and maintain KPIVs / KPOVs, control limits, and SPC monitoring strategies.

[Talent development]:

• Collaborate closely with process, equipment, and control engineers on shared packing objectives; contribute to goal setting and knowledge sharing within the team.
• Build personal technical depth in packing equipment and process; mentor technicians and support knowledge transfer within the engineering team.
• Drive cross-functional collaboration with Finishing Process, Quality, Maintenance, IT, Equipment Vendors, and corporate engineering teams.
• Foster a culture of structured problem solving, data-driven decisions, and continuous learning.

[Digital & AI Transformation]

• Support digital transformation of the Packing process - apply data analytics, anomaly detection, and machine-learning models to enhance equipment reliability, predictive maintenance, motion/servo control optimization, and smart-factory integration.
• Partner with the Digital (D^t) team to implement data pipelines, dashboards, and ML/AI applications for the packing lines.
• Promote AI-assisted root-cause analysis and algorithm/model development (Python, C/C++) for packing equipment behavior, motion control, and process optimization.

Experiences/Education - Required

• Bachelor's degree or above in Mechanical Engineering or a related engineering discipline (equipment design background is a strong plus). Candidates with shorter experience may be considered if they have a strong academic background from a top-tier university.
• 2+ years of process or equipment engineering experience in display, semiconductor, precision manufacturing, or automation equipment industry, with focus on the Packing process segment.
• Required - Industry & Equipment Experience 

o    Engineering background in Mechanical or Equipment Design; proficient with SolidWorks and mechanical simulation software for design, analysis, and verification.
o    Hands-on experience with Packing-segment equipment is strongly preferred (equipment design background is also acceptable); solid fundamentals in process control such as SPC, CPK, and KPIV/KPOV methodology.
o    Able to communicate in spoken English for cross-region collaboration; clear, logical, and well-structured communication skills.
o    Strong result orientation and ownership; proactively drives execution and delivers outcomes.

Experiences/Education - Desired

• Programming experience in Python and/or C/C++, with a track record of using them to deliver small projects or function/algorithm/model development. Experience with any one of algorithms or ML models is acceptable (please specify which models have been used).
• Proficient with servo systems, motors, drives, linear guides/rails, industrial robots and robotic manipulators; equipment commissioning, motion tuning, or automation integration experience is highly valued.
• Familiarity with data analytics tools (JMP, Minitab, SQL) and basic ML/AI concepts (supervised/unsupervised models, computer vision) is a plus.
• Ability to partner with equipment vendors, IT, and corporate digital teams to deliver end-to-end solutions.
• Master's degree in Mechanical Engineering, Mechatronics, Automation, Computer Science, or a related discipline.
• Lean Six Sigma Green Belt or Black Belt certification.
• Experience with display-glass packing processes and related automation / robotic handling equipment.
• Prior experience participating in digital transformation or automation upgrade programs at the plant level.
• Exposure to MES, PLC, IoT platforms, or edge-computing architectures.
• Demonstrated publication, patent, or sister-plant migration of engineering best practices.
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