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Middle · 4+ years exp
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Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 10, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

Google Quantum AI is building quantum computing for otherwise unsolvable problems. The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, error-corrected computations. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.

As a Hardware Engineer on the Quantum AI Fabrication team in Goleta, California, you will develop, optimize, and scale cleanroom wet chemical and solvent processes used to build superconducting quantum processors. Quantum devices are sensitive to surface interfaces, oxides, and microscopic defects, making wet processing critical to device performance and yield. In this role, you will lead process development and production sustaining across automated solvent stations, acid and base wet benches, and wafer cleaning systems for metal liftoff, photoresist strip, surface preparation, and wet chemical etching. You will design experiments to widen process windows, reduce defects and cycle time, specify and qualify new wet process equipment, and collaborate with lithography, thin film, dry etch, metrology, and operations teams to transition processes from research into production.

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

US: $132000 - $189000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Develop, optimize, and sustain cleanroom wet etch, solvent liftoff, photoresist strip, and wafer cleaning processes for superconducting quantum devices.
  • Specify, procure, qualify, and manage automated and benchtop wet processing equipment from installation through production release.
  • Monitor statistical process control (SPC) trends, lead root cause investigations for process or equipment excursions, and reduce defects.
  • Collaborate across dry etch, thin film deposition, photolithography, and metrology teams to integrate and support multi-module fabrication flows.
  • Establish process change controls, write clear standard operating procedures (SOPs), and train cleanroom technicians on development and production tools.

Qualifications

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.
  • 2 years of experience in cleanroom semiconductor fabrication.

  • 2 years of experience with wet chemical etching, solvent liftoff, photoresist strip, or wafer cleaning processes and equipment.

Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
  • 4 years of experience developing wet etch, solvent liftoff, or wafer cleaning processes in semiconductor research or manufacturing.
  • Experience qualifying and managing automated wet stations, acid or solvent benches, and chemical filtration or delivery systems.
  • Experience with defect and surface metrology (SEM, AFM, ellipsometry, particle inspection) and data analysis (Python, SQL, or JMP).
  • Experience with design of experiments (DOE), statistical process control (SPC), manufacturing execution systems (MES), or superconducting device fabrication.
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