2 years of experience in cleanroom semiconductor fabrication.
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.
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.
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.
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.

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