Software Engineer, PhD, Cloud Platforms

1 Month ago • 1 Years + • Full Stack Development

Job Summary

Job Description

Google seeks a Software Engineer with a PhD in Computer Science or a related field to join their MSCA organization. The role involves developing next-generation technologies for Google's services, handling massive-scale information processing. Responsibilities include writing and reviewing code, participating in design reviews, contributing to documentation, and troubleshooting system issues. Experience with distributed systems, concurrency, and one or more languages (C, C++, Java, Python) is required. The ideal candidate will have experience with large-scale system data analysis and debugging. The position is based in Taipei, Taiwan, and requires starting full-time in 2025.
Must have:
  • PhD in Computer Science or related field
  • Experience in C, C++, Java, or Python
  • Distributed systems experience
  • Concurrency/multi-threading
  • Code review and debugging
Good to have:
  • Large-scale system data analysis
  • Performance analysis
  • Software test engineering
  • Accessible technology development

Job Details


Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • Experience coding in one of the following programming languages including but not limited to: C, C++, Java or Python.
  • Experience in one or more of the following: architecting or developing distributed systems, concurrency, multi-threading, or synchronization.

Preferred qualifications:

  • 1 year of experience with performance, large scale systems data analysis, visualization tools, or debugging.
  • Experience in code and system health diagnosis and resolution, and software test engineering.
  • Experience developing accessible technologies.
  • Ability to start full-time role in 2025.

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

  • 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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