Hardware Validation Engineer, ML Products, Google Cloud

As a Hardware Validation Engineer, you will support end-to-end testing for machine learning hardware deployed in Google's data centers.

Google's custom-designed machines make up one of the largest computing infrastructures in the world. The Hardware Qualification team ensures that this cutting-edge equipment is reliable. In the Research & Development (R&D) lab, you plan for and execute the most effective way to test at scale. Working closely with design engineers, you give input on designs to improve our hardware until you are sure it meets Google's standards of quality, reliability, and security.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

The US base salary range for this full-time position is $105,000-$151,000 + 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

• Support creation of test plans and coordination of resources across test environments.
• Interface more executive engineers to help perform electrical, functional, performance, and reliability testing for Google's machine learning trays and solutions. Analyze results to ensure that they meet Google's requirements.
• Report bugs and propose corrective actions with cross-functional teams.
• Use scopes, protocol analyzers, BERTs, and other lab equipment to collect high precision data.
• Organize results, communicate findings, and incorporate learnings in alignment with the standards set in the qualification process.

Minimum qualifications:

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
  
• Experience working in board level design and testing.
• Experience with electrical engineering and signal integrity.

Preferred qualifications:

• Master's degree in Electrical Engineering, Computer Engineering, Physics, or a related field.
  
• Experience working in lab environments. Familiarity with lab equipment like scopes, BERTs and analyzers.
• Knowledge of low-speed interfaces like SPI and I2C, and high-speed SerDes interfaces like Ethernet and PCIe.
• Understanding of signal integrity (SI), for high speed interfaces, and best practices to collect accurate SI data.
• Ability to use scripting and automation to execute test algorithms, and then analyze results.
• Excellent communication skills.