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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
As a Staff Software Engineer on the Architecture, Analysis, Automation, and Accelerators unit, you will guide chip-system joint engineering for Google's upcoming proprietary chips.
Connecting physical layout with mass-scale data centers, you will investigate low-level operating system components and hypervisors to reduce virtualization latency across multiple compute environments. By constructing direct-hardware testing frameworks, you will pinpoint and unblock critical throughput constraints to steer downstream CPU development.
In this role, excel at untangling ambiguous runtime mysteries and partnering with cross-disciplinary engineering groups to shape the future of worldwide computing.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
- Lead hardware-system co-design for next-generation custom silicon and SoCs, translating low-level software performance insights into architectural requirements for future processor and server platforms.
- Optimize Linux kernel internals and hypervisors to systematically identify and eliminate virtualization overhead across both x86 and Arm-based hyperscale infrastructure.
- Architect bare-metal microbenchmarks, diagnostic tools, and profiling suites to isolate and resolve complex system bottlenecks spanning CPU cores, caches, and memory hierarchies.
- Drive cross-functional technical alignment across silicon architecture, platform firmware, operating system, and cloud infrastructure teams to set the performance roadmap for planet-scale workloads.
- Mentor and technically direct engineers, fostering rigorous systems performance methodologies, experimental benchmarking standards, and architectural best practices.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development and system programming.
- Experience with Linux kernel internals, kernel virtualization, or hypervisor development.
- Experience in performance analysis, debugging, and system optimization on server architectures.
Preferred qualifications:
- Master's degree or PhD in Computer Engineering, Computer Science, or Electrical Engineering.
- Experience with Kernel-Based Virtual Machine (KVM), two-level paging, VM-exit optimization, vCPU scheduling, and bare-metal microbenchmarks.
- Experience with hardware/software co-design and collaborating with cross-functional teams to influence SoC/CPU feature specifications.
- Expertise in virtualization performance characterization and root-causing virtualization overheads on enterprise server platforms.