Hardware Engineer

About the Job

The US base salary range for this full-time position is $150,250 - $189,000 + 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.

Position reports to the Google Mountain View, CA office & may allow for a hybrid schedule as per Google policy.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Responsibilities

• Analyze hardware failures to identify root causes and implement corrective solutions for key issues and risks.
• Optimize complex hardware components for performance, power, and cost by applying engineering best practices.
• Review hardware designs, including schematics, layouts, and block diagrams, to proactively identify and mitigate potential risks.
• Validate design specifications and performance through rigorous measurements, simulations, and testing.
• Document the hardware design, implementation processes, and validation results throughout the entire product lifecycle. Collaborate with cross-functional teams to meet performance requirements for complex hardware subsystems.

Qualifications

Minimum qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Engineering, Mathematics, Physics, or a related field and 2 years of experience in the job offered or in a Hardware Engineer-related occupation.
• Position requires 2 years of experience in the following: Troubleshooting and debugging complex hardware, software, and firmware system failures using root cause analysis or failure analysis; Data analysis or statistical analysis to evaluate system performance and generate technical solutions; Technical documentation of complex hardware and software specifications; Hardware subsystem design and validation; and Image Quality Metrics Development in Python or C++.