Hardware Validation Lab Engineer, Google Cloud

1 Day ago • 1-3 Years • Research & Development

Job Summary

Job Description

This Hardware Validation Lab Engineer role at Google Cloud in Bengaluru, India, involves supporting new product engineering and development in Google's R&D labs. Responsibilities include designing and building system-level testbeds, maintaining lab infrastructure, collaborating on software and hardware systems, developing methodologies and tools, coordinating lab-engineering interactions, resolving challenges, generating implementation plans, and providing technical guidance during deployments. The ideal candidate will have experience in a hardware engineering environment, familiarity with Linux, networking, and data center servers, and excellent communication and time management skills. The role contributes to the development of custom silicon solutions for Google's direct-to-consumer products.
Must have:
  • Bachelor's degree in relevant field
  • 2+ years hardware engineering experience (or 1 year with advanced degree)
  • Linux, networking, troubleshooting experience
  • Data center server experience
  • System-level testbed design & build
  • Excellent communication & time management
Good to have:
  • Data center/network operation experience
  • Understanding of computer systems (physical, functional, etc.)
  • Network design, protocols, troubleshooting knowledge
  • Python or scripting language proficiency

Job Details

Minimum qualifications:

  • Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
  • 2 years of experience working in a hardware engineering technical environment, or 1 year of experience with an advanced degree.
  • Experience with Linux, networking, network troubleshooting, failure diagnosis, data center server, debugging/troubleshooting.

Preferred qualifications:

  • Experience in working within a data center or networking operation center environment.
  • Understanding of computer systems: physical, functional, logical, mechanical, electrical, software, thermal etc.
  • Understanding of network design, protocols, and troubleshooting.
  • Ability to read and write code in Python or scripting language.
  • Excellent time management skills with an ability to manage constant priority changes and deadlines.
  • Excellent written and verbal communication skills.

About the job

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

In this role, you will support new product engineering and development in Google’s hardware Research and Development labs by helping to design, build, and maintain system-level testbeds (think data center-scale). Our engineering lab team performs work that allows product development teams to focus on development.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Responsibilities

  • Help design and build system-level testbeds and maintain lab space, tools and infrastructure.
  • Work with teams to develop software and hardware systems and develop methodologies and tools to support team members.
  • Coordinate the interactions between labs and engineering.
  • Resolve challenges by applying knowledge and skills, escalating design, manufacturing and product test issues to other people within the organization when appropriate.
  • Generate implementation plans and provide technical expertise and guidance during deployment activities.

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