Staff Semiconductor Thin Films Process Engineer, Raxium

Google's Raxium display group has established a revolutionary semiconductor materials display technology that enables new functionality in display products, bringing to users a closer and more natural linkage between the digital and physical realms in applications such as augmented reality (AR) and light-field display. With start-up roots and a state-of-the-art compound semiconductor fab in Silicon Valley, Raxium is seeking to build upon its engineering team with an aim to disrupt next-generation display markets.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $188000 - $275000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Develop and sustain new processes associated with thin film deposition tools including sputtering, PECVD, e-beam, PVD, and others.
• Manage process control and defectivity reduction to deliver yield improvements. 
• Work with the Process Engineering team to select our next generation of tools needed for volume manufacturing.
• Collaborate with the Integration team to develop new process capabilities that address new design requirements.

Minimum qualifications:

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
  
• 5 years of experience in the semiconductor industry maintaining equipment, such as ICP, PVD, or CVD.
• Experience with conventional microfabrication techniques, including lithography, etch, thin-film deposition, and metrology.
• Experience with data analysis and reporting.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
  
• Experience in data analysis in quality reliability (tools like JMP).
• Experience with microdisplay or microLED technology.
  
• Understanding of statistical process control and process improvement, including implementation experience.