Hardware Engineer

About the Job

The Google Quantum Hardware team is building a quantum computer using superconducting integrated circuits. Here, you have the opportunity to work hands-on with an entirely new paradigm of computing as it advances from fundamental physics to industrial applications. These devices are extremely sensitive to materials properties, and so improving device performance requires creative fabrication techniques.

The US base salary range for this full-time position is $201,300 to $231,000 + 15% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google.

Responsibilities

• Identify hardware flaws, analyze key risks or trade-offs, and implement corrective solutions
• Evaluate hardware design feasibility against product requirements and collaborate with partners to scope projects
• Apply best practices to optimize complex hardware components for performance, power, and cost
• Predict hardware design consequences in cross-functional trade-off discussions using simulation or measurement data
• Review and approve hardware designs, resolve test issues, and compare performance against predictions. Drive the documentation of hardware design, implementation, and validation results throughout the product life cycle

Qualifications

Minimum qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field and 5 years of progressive, post-baccalaureate experience in the job offered or in a Hardware Engineer-related occupation.
• Alternatively, will accept a Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, and 3 years of experience in the job offered or in a Hardware Engineer-related occupation.
• Position requires 3 years of experience in the following: System-level analysis of component interrelations, trade-offs, and systems architecture to optimize system testability, performance, reliability, and cost. Identifying, debugging, triaging, and conducting root-cause analysis of technical issues. Analyzing data and information to generate solutions, identify system/workflow gaps, and develop plans of action. Applying domain-specific technical knowledge (Optics, Sensors, Audio/Digital Signal Processor) to complete work. Managing the product lifecycle (development, maintenance, evolution, delivery, and sunsetting);