Software Engineer III, Performance, Google Cloud

1 Month ago • 2 Years + • DevOps • Full Stack Development • Backend Development

Job Summary

Job Description

This Software Engineer III role focuses on performance within Google Cloud. Responsibilities include participating in design reviews, code review, debugging and resolving system issues, developing automations and tooling, and collaborating on performance and reliability issues involving massive datasets. The ideal candidate will have experience with software development, data structures and algorithms, large-scale infrastructure, and distributed systems. Experience with Unix/Linux, big data, and security is preferred. The role contributes to the development of next-generation technologies handling information at massive scale.
Must have:
  • Bachelor's degree or equivalent
  • 2+ years software development experience
  • 2+ years data structures/algorithms experience
  • 2+ years large-scale infrastructure experience
  • Design review participation
  • Code review and feedback
  • Debugging and issue resolution
Good to have:
  • Master's/PhD in CS
  • Unix/Linux experience
  • Distributed/parallel systems experience
  • Big data experience
  • Security software development 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 in either an academic or industry setting.
  • 2 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience working with two or more from the following: Unix/Linux environments, distributed and parallel systems, information retrieval, networking, developing large software systems, streaming or batch big data analysis, workflow orchestration tools, and/or security software development
  • Experience with data analysis and big data.

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

  • 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).
  • 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.
  • Contribute to further development of automations and tooling.
  • Collaborate on performance and reliability issues involving massive amounts of data and information.

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