Responsibilities
Plan and execute detailed analysis of CPU workloads within the Google Cloud infrastructure, analyze trends and map future requirements.
Collaborate closely with architecture and modeling owners to understand design specifications and identify critical scenarios related to CPU performance and efficiency.
Develop and implement custom workload generation tools and methodologies to simulate real-world usage patterns on Google Cloud platforms.
Analyze the impact of machine learning applications on CPU usage, identifying opportunities for optimization and feature enhancements.
Lead the investigation and development of metrics to measure CPU performance and efficiency, presenting findings to stakeholders and contributing to strategic decisions.
PhD in Electrical and Electronics Engineering, or equivalent practical experience.
2 years of experience with software development in C++ programming language.
1 years of experience with data structures or algorithms.
Preferred qualifications:
Experience in performance modeling, performance analysis, and workload characterization.
Experience applying machine learning techniques and inference usage models on hardware.
Expertise in CPU architecture disciplines such as branch prediction, prefetching, value prediction, and caching policies.