Senior Software Engineer, Infrastructure
Job Description
- Master's/PhD in CS
- Technical leadership experience
- Experience with accessible technologies
- 5+ years software development (C++)
- Data structures/algorithms expertise
- Experience with distributed systems/networks
- Networking component development
- Linux kernel code development
- Software testing & maintenance
- Bonus
- Equity
- Benefits
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in C++; and with data structures/algorithms
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with developing infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
- Experience building networking components and products (e.g., load balancers, firewalls, NAT, SDN, switches/routers, CDN, network protocols, or caching).
- Experience developing and debugging Linux kernel code.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
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
- Write and test 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.
