SW Applications Engineer

About the role

The SW Applications Engineer works in the Process Diagnostics and Control (PDC) group, developing advanced imaging, AI algorithms and data‑product solutions that detect and classify nanometer‑scale defects in semiconductor manufacturing.

Key responsibilities

• Maximize performance of data products by understanding customer use‑cases and collaborating with R&D, algorithms and product teams.
• Extend applicative expertise across multiple data sources (CAD, design, process, inspection) and ensure software readiness for field deployment.
• Drive adoption of data‑product solutions at leading fabs worldwide and act as the technical escalation point for complex field issues.
• Develop Python utilities and scripts for debugging, workflow automation and issue isolation.
• Conceptualize and prototype technical flows that convert multi‑source data into new applications and insights.
• Translate Voice of Customer feedback into concrete product requirements and roadmap inputs.
• Explore and validate AI/ML‑based approaches to advance PDC’s data‑product capabilities.

Required profile

• Master’s or Bachelor’s degree in Electronics Engineering, Computer Science, VLSI or a related field.
• 2–5 years of experience in semiconductor process and defectivity, with hands‑on knowledge of CAD and design‑based inspection concepts.
• Willingness to travel up to 50 % of the time to global semiconductor fabs.
• Strong analytical and problem‑solving skills, able to work independently and within cross‑functional teams.
• Excellent communication skills for interaction with customers, field teams and R&D engineers.

Required skills

• Proficiency in Python for scripting and tool development.
• Familiarity with AI/ML concepts and practical experience applying them to data analysis or product development.
• Experience with GenAI‑assisted development tools such as Claude or Copilot.
• Knowledge of CAD and design‑based inspection workflows.

What we offer

• Opportunity to work on cutting‑edge semiconductor technology and data‑product solutions.
• Direct collaboration with customers and global R&D teams, with real influence on product roadmaps.
• Dual career track: technical specialist or engineering leadership.
• A culture of ownership, innovation and continuous learning.