Hardware Engineer, Surface Science and Engineering, Quantum AI
Job Summary
Job Description
This Hardware Engineer role at Google Quantum AI involves optimizing fabrication processes using advanced surface analysis techniques (AFM, AFM-IR, SIMS, TDS, XPS, SEM/EDX). Responsibilities include developing characterization techniques for thin films and surface defects, designing and executing experiments, designing experiments for surface treatment processes, and working with device teams to improve device performance. The ideal candidate will have experience with surface treatment and analysis in semiconductor fabrication, vacuum equipment, and data analysis software. This is a crucial role in improving the performance and reliability of quantum computing devices.
Must have:
- Bachelor's degree in relevant field
- 3+ years experience in semiconductor fabrication
- Surface treatment & analysis experience
- Vacuum/UHV equipment handling
- Data analysis & DOE design
Good to have:
- PhD degree
- 5+ years experience
- Etching & cleaning experience
- SOP writing
- Excellent communication skills
Perks:
- Bonus
- Equity
- Benefits
4 skills required
Job Details
Minimum qualifications:
- Bachelor's degree in materials science, physics, chemistry, spectroscopy, or a related field.
- 3 years of experience in research and development with material process and analysis in semiconductor fabrication field in a clean room environment.
- Experience in surface treatment and analysis using different sources and techniques.
- Experience in handling vacuum and ultra-high-vacuum equipment.
Preferred qualifications:
- PhD degree in materials science, physical chemistry, physics, spectroscopy, or cross trained related fields, or equivalent practical experience.
- 5 years of experience in research and development or production environments with surface treatment and analysis skills in the semiconductor fabrication field.
- Experience in handling vacuum and ultra-high-vacuum equipment for etching, cleaning, treatment, and analyzing surface/interface chemistry and structures.
- Experience with data analysis software, process control, and SOP writing.
- Excellent communications and presentation skills.
About the job
Google Quantum AI's mission is to build and unlock solutions to problems, and the team's roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.As a hardware engineer, you will bring your surface analysis experience to help optimize fabrication processes using characterization techniques. The advanced investigative techniques, such as AFM, AFM-IR, SIMS (D-SIMS and TOF-SIMS), TDS, XPS, SEM/EDX, will be your key tools in accomplishing your daily tasks. You will also be comfortable with developing prototypes for surface treatment (using plasma and ion-beams) with in-situ analysis devices, maintaining, and stabilizing the process flow and equipment. This role is crucial to our success as we continue to improve the performance, coherence, and reliability of our devices.
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 $147,000-$216,000 + bonus + equity + benefits. Transfer compensation is determined algorithmically and is non-negotiable. Your recruiter will share more about the specific salary for your targeted location during the hiring process. Learn more about , , and about benefits at Google at .
Responsibilities
- Develop strategy and detailed characterization techniques and procedures for thin films, surface defects, surface/interface chemistry, and materials structures.
- Design and execute experiments using instruments such as AFM, AFM-IR, SIMS (D-SIMS and TOF-SIMS),TDS, XPS, SEM/EDX, including data analysis.
- Design and execute the design of experiments (DOEs) for surface treatment and analysis processes to reduce surface contamination and defects.
- Work with device and fabrication teams to correlate analysis results with device performance, fabrication procedures, and co-develop strategies for device performance improvements.
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