Senior Software Engineer, Google Cloud Compute
Job Summary
Job Description
- 5+ years software development experience
- 3+ years Go (Golang) experience
- Linux system administration experience
- Experience with data structures/algorithms
- Design and build high-scale infrastructure
- Master's degree in CS
- Experience with performance analysis
- Technical leadership experience
- Experience developing accessible technologies
- Bonus
- Equity
- Benefits
9 skills required
Job Details
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- 3 years of experience working with operating systems.
- 3 years of experience with Go (Golang).
- Experience with Linux system administration.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 2 years of experience with performance, large scale systems data analysis, visualization tools, or debugging.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
- Proficiency in code and system health, diagnosis and resolution, and software test engineering.
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.
The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .
Responsibilities
- Design, build, and own the high-scale infrastructure delivering secure and reliable Linux images globally.
- Drive technical strategy and implement solutions by collaborating with major OS vendors and internal Google Cloud teams to enhance GCE's foundational compute layer.
- Collaborate with internal teams to integrate new platform features into the guest environment.
- Develop, test, and maintain vital in-guest software, ensuring consistency, security, and performance across operating systems.
- Lead initiatives addressing complex challenges such as OS lifecycle management, automated validation across machine types and security hardening.
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