Senior Hardware Qualification Engineer, Machine Learning, Google Cloud
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Minimum qualifications:
- Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
- 4 years of experience working in a data center technical environment, or 3 years of experience with an advanced degree.
- Experience with testing requirements, best practices, and algorithms for data center hardware or systems, and using scripting and automation to execute test algorithms and analyze results.
- Experience with lab equipment (e.g., scopes, analyzers) to collect traces.
Preferred qualifications:
- Master's or PhD degree in Electrical Engineering, Computer Engineering, Physics, or a related field.
- 1 year of experience in technical leadership.
- Experience with scripting and automation to execute test algorithms, and then analyze results with knowledge of lab equipment like scopes, Bidirectional Encoder Representations from Transformers (BERTs) and analyzers.
- Experience determining the appropriate data to collect to facilitate failure analysis from vendors.
- Experience with Machine Learning/Graphics Processing Unit (ML/GPU) hardware components, memory systems, and interconnect technologies.
- Knowledge of signal integrity, high speed interfaces, and to collect accurate Systems Integrator (SI) data.
About the job
Google's custom-designed machines make up one of the largest computing infrastructures in the world. The Hardware Qualification team ensures that this equipment is reliable. In the Research and Development lab, you plan for and execute the most effective way to test at scale.
In this role, you will lead initiatives to do end-to-end testing for machine learning hardware deployed in Google's data centers. You will give input on designs to improve our hardware until you're sure it meets Google's standards of quality, reliability, and security.Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
- Create, test, plans and coordinate resources across test environments.
- 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 motivate corrective action where needed with external suppliers and internal Supply Quality Engineer (SQEs), commodity teams and developers.
- Use scopes, protocol analyzers, Bidirectional Encoder Representations from Transformers (BERTs) and other lab equipment to collect precision data.
- Organize results, communicate findings and incorporate learnings to maintain and improve the qualification process.
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