Fabrication Data and Yield Hardware Engineer, Quantum AI

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.
  
• 1 year of experience with conventional micro fabrication characterization techniques.
• 1 year of experience with data analysis and experiment planning.
• 1 year of conventional micro fabrication process techniques, including lithography, deposition, or etching.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
  
• Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• Experience with data analysis software such as numpy/pandas, R, or JMP.
• Understanding of semiconductor fabrication processes and equipment.

About the job

Quantum computers will leverage the laws of quantum mechanics to solve some previously intractable problems, but they also require a lot of non-quantum engineering to build a complete system. This role is critical to optimizing our fabrication processes and maximizing yield. In this role, you will be responsible for analyzing production data to identify trends, pinpoint root causes of yield loss, and develop data-driven solutions for improvement. You will collaborate with process engineers to implement process optimizations, equipment modifications, and development of new technologies. Additionally, you will will develop and maintain data analysis tools, visualizations, and dashboards to provide actionable insights to the wider team.

The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, error-corrected computations. Google Quantum AI's mission is to build this computer and unlock solutions to classically intractable problems. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.

The US base salary range for this full-time position is $126,000-$181,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Analyze production data to identify root causes of yield loss and implement data-driven solutions for improvement.
• Develop and maintain data analysis tools, visualizations, and dashboards to track key metrics and provide actionable insights.
  
• Perform failure analysis to understand yield-limiting factors and recommend corrective actions.
• Collaborate with process engineers to optimize processes, implement equipment modifications, and introduce new technologies for yield enhancement.
• Monitor critical process parameters and implement statistical process control (SPC) methods to ensure process stability.