INSP Process Engineer

Key Responsibilities

Inspection equipment and process support

• Supports daily performance, reliability, and continuous improvement of inspection equipment and operations.
• Supports inspection equipment, controls, and process improvements to enhance operational performance.
• Supports the design, modification, and improvement of automated equipment and motion-control systems to meet or exceed operational requirements.
• Lead structured root-cause investigations and drive containment, corrective actions, and continuous improvement; drive containment, fundamental understanding, and permanent corrective actions.
• Define and maintain performance-monitoring and statistical quality-control approaches.

Talent development

• Collaborate with cross-functional engineering teams on shared equipment and operational objectives; contribute to goal setting and knowledge sharing within the team.
• Build personal technical depth in Inspection equipment and process; mentor technicians and support knowledge transfer within the engineering team.
• Collaborate with relevant engineering, quality, maintenance, digital/IT, and qualified supplier teams.
• Foster a culture of structured problem solving, data-driven decisions, and continuous learning.

Digital & AI Transformation

• Support the use of digital tools and data analytics to improve manufacturing equipment and operational performance.
• Apply approved data analytics and digital technologies to support equipment reliability, maintenance effectiveness, and operational improvement.
• Partner with digital, IT, and engineering teams to Implement data solutions, reporting tools, and approved digital applications that support manufacturing operations.
• Support approved software, analytics, and automation solutions for equipment and process improvement. 

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 Inspection process segment. 
• Mechanical or equipment-engineering background with experience using CAD and engineering-analysis tools for design, analysis, and verification.
• Experience supporting automated equipment, manufacturing operations, or quality inspection systems is preferred (equipment design background is also acceptable);Knowledge of statistical process control, process capability, and data-driven problem solving.
• Able to communicate in spoken English for cross-region collaboration; clear, logical, and well structured communication skills.
• Strong result orientation and ownership; proactively drives execution and delivers outcomes. 

Experiences/Education - Desired

• Programming experience in Python, C/C++, or similar languages for engineering, automation, or data-analysis applications. Familiarity with machine-learning concepts or applied analytics is a plus.
• Experience with industrial automation, motion-control systems, equipment commissioning, or equipment integration is preferred; 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 in automated inspection, precision manufacturing, or related industrial automation environments.
• Prior experience participating in digital transformation or automation upgrade programs at the plant level.
• Familiarity with manufacturing digital systems, industrial automation technologies, or data integration tools.
• Demonstrated technical contributions, innovation experience, or continuous-improvement achievements, consistent with applicable confidentiality obligations.