Software Engineer, GPU System, Google Cloud Platforms

1 Month ago • 2 Years + • Research & Development

Job Summary

Job Description

This Software Engineer role at Google focuses on developing, integrating, debugging, and validating Data Center Graphics Processing Units (GPUs) system software. Responsibilities include resolving GPU machine issues, integrating and validating GPU kernel drivers and firmware, collaborating with cross-functional teams to improve reliability and stability, writing software architecture specifications, and developing comprehensive test suites. The position requires experience in embedded systems, C/C++ programming, Linux/Unix environments, and working with GPUs and related peripherals. The ideal candidate will also possess skills in developer operations, release management, and scripting languages.
Must have:
  • Bachelor's degree in CS or related field
  • 2+ years embedded system software development experience
  • 2+ years C/C++ coding experience
  • Linux/Unix development environment experience
  • GPU system software development, integration, debugging, and validation
Good to have:
  • Experience with developer operations, release management, and integration testing
  • Device driver design and development for peripherals (GPUs, PCIe, I2C, USB)
  • Python or scripting language experience
  • Open source development experience

Job Details


Minimum qualifications:

  • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  • 2 years of experience in embedded system software development.
  • 2 years of experience coding in C or C++.
  • Experience with Linux/Unix development environments.

Preferred qualifications:

  • Experience with developer operations, release management, and integration testing.
  • Experience with designing and developing device drivers for peripherals (e.g., GPUs, PCIe Switches, and connectivity buses like I2C, USB, PCIe).
  • Experience coding in Python or with scripting languages (e.g., shell).
  • Experience with open source development.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

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

  • Develop, integrate, debug and validate Data Center Graphics Processing Units (GPUs) system software, resolve Data Center GPU machines issues.
  • Integrate and validate GPU kernel drivers and firmware, enabling GPU Software bundle on the Data Center machines.
  • Collaborate with Google Cloud cross-teams to enable software and solve the issues, improve Data Center GPU machines reliability, stability and repairability.
  • Write detailed specifications for software architecture and GPU systems we build.
  • Develop comprehensive test suites that enable unit, integration, and system level testing of our system software.

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