Semiconductor Process Engineer – Autonomous Experimentation & AI for Nanofabrication Facilitiescoming soon

The MOSIS 2.0 PIES Team is Hiring

Background

The California Defense Ready Electronics and Microdevices Superhub (California DREAMS) will promote innovation and lab-to-fab transition for RF and other technologies in the Southern California region. MOSIS 2.0 will play a critical role in providing access to university nanofabs and industry prototyping and production fabs in support of rapid prototyping for Government- and Industry-funded R&D projects. The primary end uses for the service span from advanced RF-spectrum communications and sensing applications such as 5G/6G and related domains to advanced digital design. The Prototype Integration and Engineering Services (PIES) team will operate within MOSIS 2.0 to provide engineering support for users bridging the valley between innovations and production.

MOSIS 2.0 PIES team is hiring a Semiconductor Process Engineer that will be part of a core team at USC/ISI complemented by a distributed team at our partner university labs and industry fabs. We are seeking a highly motivated semiconductor process engineer with a strong background in artificial intelligence (AI) and machine learning or robotics. The ideal candidate will drive the development of autonomous experimentation processes and optimize semiconductor fabrication flows at USC’s Nanofabrication Facility. This role integrates cutting-edge AI methodologies into traditional process engineering to enhance yield, efficiency, and innovation.

Location

California (On-site at the USC University Park Campus)

Position Type

Full-Time, Research/Support Role, MOSIS 2.0 (California DREAMS Microelectronics Commons) / USC ECE Department.

Responsibilities

• Process Development & Optimization
  • Design, implement, and optimize semiconductor fabrication processes by integrating AI models and machine learning algorithms.
  • Develop autonomous experimentation flows to enable real-time process control and optimization.
• Data Analysis & Automation
  • Collect, analyze, and interpret process data to identify trends and drive continuous improvement.
  • Collaborate with software developers and process engineers to create automated control platforms and reporting systems.
• Research and Collaborative Projects
  • Work closely with USC ECE department researchers and facility staff to support funded research projects in nanofabrication.
  • Contribute to technical papers, research reports, and presentations that document the integration of AI into process control.
• Training and Technical Support
  • Provide training and technical support to facility personnel on AI-enabled process control systems and autonomous workflows.
  • Assist in the troubleshooting and scaling of new process flows from laboratory settings to high-volume production.

Qualifications

• Educational Background
  • Bachelor’s, Master’s, or PhD in Electrical Engineering, Materials Science, Chemical Engineering, or a related field.
• Professional Experience
  • At least 3 years of hands-on experience in semiconductor process engineering.
  • Demonstrable experience in applying AI, machine learning, or statistical process control to manufacturing processes.
• Technical Skills
  • Proficiency in programming languages (e.g., Python, MATLAB, or R) and familiarity with machine learning frameworks.
  • Strong knowledge of semiconductor fabrication techniques (e.g., photolithography, etching, deposition, metrology).
• Analytical and Communication Skills
  • Excellent problem-solving skills and a data-driven mindset.
  • Strong written and verbal communication skills with the ability to articulate complex technical concepts to diverse audiences.
• Collaborative Spirit
  • Proven ability to work in interdisciplinary teams and support research-driven projects.