Software Engineer, Performance Evaluation

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  
• Experience in Architecture performance analysis and optimization.
• Experience in Computer Architecture.
• Experience working with Python or C++.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
  
• Experience developing accessible technologies.
  
• Proficiency in utilizing architectural performance simulation models, pre-silicon, and post-silicon platforms for analysis and debugging.

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.

Our team is focused on finding performance issues and optimizing using hardware and software recommendations that can be implemented for Google servers with a view to a full end-to-end solution.

• Utilize expert knowledge of hardware pipelines, driver stacks, and platform architecture to drive performance analysis and optimization.
• Recommend hardware and software architectural improvements, with performance ROI justification, to bridge engaged gaps and build ARM servers.
• Define performance metrics and counters for debugging, profile workloads, and classify them based on relevant characteristics.
• Conduct driver-based emulation performance validation, including environment bring-up, benchmarking, workload profiling/characterization, engaged analysis, bottleneck identification, and debugging of industry-standard benchmarks, open-source workloads, and internal Google applications.