Principal Digital Twin Engineer, Manufacturing

The challenge

Advanced-node process qualification cycles take over a year. A digital twin of the lithography and etch processes could compress this significantly by simulating process parameter variations digitally before committing silicon.

Role overview

Digital twins combining physics-based models of semiconductor manufacturing processes with real-time sensor data from the fab floor. The models predict how process parameter changes affect yield before those changes are physically implemented -- reducing qualification cycles and improving first-pass yield.

Specializations

Technical requirements

• PhD in Chemical Engineering, Materials Science, Physics, or related field with modeling focus
• 8+ years in process modeling or digital twin development, with 3+ years in semiconductor or precision manufacturing
• Experience combining physics-based models with data-driven techniques (hybrid modeling)
• Proficiency in Python, MATLAB, and at least one physics simulation framework (COMSOL, Ansys, or domain-specific)
• Understanding of semiconductor process flows (lithography, etch, deposition, CMP)
• Experience with time-series databases and streaming data architectures

Key responsibilities

• Design and build digital twin models of semiconductor lithography, etch, and deposition processes
• Integrate physics-based process models with real-time IoT sensor data from fab tools
• Develop calibration workflows that keep digital twin models aligned with physical process drift
• Build simulation environments that predict yield impact of process parameter variations
• Create dashboards and APIs that process engineers use to query the digital twin
• Define the data architecture for real-time model inputs (tool sensors, metrology, defect inspection)

Compensation & Benefits

• Base salary: $190,000 - $230,000
• RSU grant with annual refresh
• Annual bonus 15%
• Relocation package to Austin area
• On-site fitness center, meals, and child care