Software Engineer III, XBorg, Google Cloud

20 Hours ago • 2 Years + • Artificial Intelligence

Job Summary

Job Description

As a Software Engineer III at Google, you'll contribute to XBorg, a novel orchestration layer for scheduling throughput-oriented workloads, focusing on ML training and inference. Responsibilities include writing and reviewing code, participating in design reviews, contributing to documentation, and troubleshooting system issues. You'll work with technologies like weighted fair queuing and contribute to increased resource efficiency for ML workloads across major Alphabet products. The role requires experience in software development, data structures, and algorithms. The ideal candidate possesses a Master's or PhD in Computer Science and experience with accessible technologies and ML infrastructure.
Must have:
  • Software development experience
  • Data structures and algorithms expertise
  • Code review and debugging skills
  • Contribution to documentation
Good to have:
  • Master's/PhD in Computer Science
  • Experience with accessible technologies
  • Machine Learning infrastructure experience

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  • 2 years of experience with data structures or algorithms.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience developing accessible technologies.
  • Experience with Machine Learning infrastructure.

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.

XBorg is part of Borg Control Plane and is a novel orchestration layer responsible for scheduling of throughput oriented workloads onto clusters across the fleet, with a central focus on Machine Learning (ML) training and inference workloads. Xborg's features and introduction of new concepts, such as weighted fair queuing and seamless opportunistic access to unused resource, spatial and platform flexibility, etc. have led to increased resource occupancy and efficiency for ML workloads across major Alphabet products.

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

  • Write product or system development code.
  • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

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