Process Engineer IV – AI / Machine Learning

Applied Materials • Santa Clara, CA

3d

About The Position

Design and deploy machine learning models to automate repetitive data sorting, trend detection, and limit setting for process and material specifications. Improve engineering efficiency and product robustness by identifying root causes of recurring design and supplier quality issues through data-driven analysis. Drive AI adoption across process engineering by developing and applying scalable data analysis models and methodologies. Define display equipment requirements and review manufacturing process techniques to support new product introduction and production ramp. Design and analyze data collection plans for moderately complex process experiments; compile technical reports and present findings to cross-functional stakeholders. Perform hardware and process characterization, including thin-film property measurement and system-level evaluation. Apply ML/AI methodologies beyond core R&D, extending to equipment automation and other advanced manufacturing applications. Act as a technical resource and mentor for less experienced engineers while operating with minimal supervision.

Requirements

• Ph.D. in Materials Science, Chemical Engineering, Chemistry, or Physics with 7+ years of industry experience, or Master's degree in the same fields with 10+ years of industry experience.
• Strong foundation in materials science, chemical engineering, physics, data science, or engineering data science.
• 3+ years of experience in semiconductor or display manufacturing environments
• Working knowledge of semiconductor or display fabrication equipment and fab process requirements.
• Demonstrated experience applying ML/AI techniques to improve engineering processes, products, or services.

Nice To Haves

• Coding experience for data processing and model development is preferred.

Responsibilities

• Design and deploy machine learning models to automate repetitive data sorting, trend detection, and limit setting for process and material specifications.
• Improve engineering efficiency and product robustness by identifying root causes of recurring design and supplier quality issues through data-driven analysis.
• Drive AI adoption across process engineering by developing and applying scalable data analysis models and methodologies.
• Define display equipment requirements and review manufacturing process techniques to support new product introduction and production ramp.
• Design and analyze data collection plans for moderately complex process experiments; compile technical reports and present findings to cross-functional stakeholders.
• Perform hardware and process characterization, including thin-film property measurement and system-level evaluation.
• Apply ML/AI methodologies beyond core R&D, extending to equipment automation and other advanced manufacturing applications.
• Act as a technical resource and mentor for less experienced engineers while operating with minimal supervision.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree