Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. 5 years of experience with software development in C++ programming language or 4 years of experience with an advanced degree. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 5 years of experience with data structures and algorithms. Experience in modern CPU/Machine Learning (ML) architecture and micro-architecture. Ability to learn coding languages. Excellent object-oriented database design and SQL skills. 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. In this role, you will work at the center of Google’s most strategic infrastructure investments. You will join a high-impact team operating on the critical path of Google’s hardware and software evolution, bridging the gap between cutting-edge compute infrastructure and the massive scale of Google’s software stack. You will be responsible for defining the methods and technologies required to model, simulate, and analyze complex hardware systems, with a core focus on security, performance, and correctness analytics, ensuring the efficiency of our future compute platforms. As a software engineer in this group, you will act as an architect, designer, and coder—taking ownership of your goal and working in close partnership with cross-functional teams to make it a reality. In this role, you will sit at the intersection of hardware design and software optimization for Google's next-generation high-performance compute cores. You are not just supporting existing infrastructure, helping build the foundation of future hardware, as this work is on the "most critical path" for Google’s strategic future. You will have visibility into and influence over the core technology that powers our most intensive services. You have the rare opportunity to bridge the gap between silicon-level security research and massive-scale software implementation, working with experimental AI tools that are shaping how we verify and optimize future hardware.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 behind Google's groundbreaking innovations, empowering the development of 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. Responsibilities Drive end-to-end performance modeling and analysis for next-generation CPUs, while identifying architectural bottlenecks, ensure system correctness, and implement rigorous optimization strategies across the hardware-software stack to maximize efficiency for large-scale compute workloads. Design, develop, and maintain advanced software modeling tools and simulation environments, leverage C++, Python, and experimental AI-driven methodologies to perform deep-dive studies and automate analytical workflows. Conduct in-depth security analysis and threat modeling for hardware-software interfaces, while developing and implementing methodologies for detecting, mitigating, and analyzing side-channel and micro-architectural vulnerabilities, ensuring our systems meet the highest standards of safety and privacy. Explore, deploy, and scale experimental AI-driven tooling to automate verification workflows, enhance predictive modeling, and accelerate development cycles, actively contribute to expanding the team's suite of AI-assisted capabilities. Provide technical leadership in complex system integration projects, guide cross-functional teams to resolve large-scale compute bottlenecks, influence architectural designs, and facilitate the successful deployment of hardware-software solutions.