Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- Experience programming in one or more of the following languages: Ruby, Python, Java, C++.
- Experience with performance evaluation.
- Experience in Performance analysis.
- 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.
- Experience with implementing software and hardware performance fixes.
- Experience with HardWare and SoftWare emulation performance validation.
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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.
Responsibilities
- 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.
- Lead the pre-silicon emulation and hardware-software co-validation of Google's next-generation ARM server processors.
- Conduct driver-based emulation performance validation, including environment bring-up, milestone planning, benchmarking, workload profiling/characterization, competitive analysis, bottleneck identification, and debugging of industry-standard benchmarks, open-source workloads, and internal Google applications.
- Recommend hardware and software architectural improvements, with performance ROI justification, to bridge engagedgaps and build ARM servers.