Software Engineer II, Cluster Management, Borg

1 Month ago • 1 Years + • Full Stack Development • Backend Development

Job Summary

Job Description

This Software Engineer II role focuses on improving Google's Borg cluster management system. Responsibilities include understanding guest and host environments to develop secure solutions, collaborating on software feature optimization, developing, testing, and releasing solutions, and building infrastructure for performance metric measurement. The ideal candidate will have experience with large-scale infrastructure, distributed systems, and programming languages like Python, C++, or Go. The role contributes to enhancing Borg's efficiency, scalability, and security, supporting Google's vast services and Google Cloud's offerings.
Must have:
  • 1+ year software development experience
  • Experience with data structures/algorithms
  • Large-scale infrastructure/distributed systems experience
  • Develop, test, integrate, and release software solutions
  • Understand guest and host environments
Good to have:
  • Concurrency, multithreading, and synchronization experience
  • Experience with Rust, C, C++, Python, or Go
  • Knowledge of Linux Internals, Kernel, and Virtualization

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 1 year of experience with data structures or algorithms.
  • 1 year of experience building and developing large-scale infrastructure or distributed systems.

Preferred qualifications:

  • Experience in concurrency, multithreading and synchronization.
  • Experience with software development in Rust, C, C++, Python, or Go.
  • Experience or knowledge of Linux Internals, Kernel, and Virtualization.

About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

Our mission is to improve Borg's efficiency, make it easy to use, scalable and secure.

Our team that makes sure that more GPUs and TPUs capacity is there for even better models, services and solutions.

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

  • Understand guest (virtualized) and host (hypervisor) environments and come up with secure solutions that connect both.
  • Work with peers to identify, design, create and optimize software features that run on top of Google's hardware stack.
  • Develop, test, integrate, and release these solutions.
  • Design and build infrastructure to automatically measure and detect regressions in key performance metrics at scale.

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