Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 7 years of experience building and developing infrastructure, distributed systems, networks, compute technologies, storage, or hardware architecture.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
- Experience working with Hardware and Software teams developing complex SoC’s.
- Experience in correlating modeled performance with RTL/Emulation/Silicon.
- Experience leading project teams and setting technical direction.
- Knowledge of one or more of the following areas: CPU, Cache, Interconnect, DRAM, or PCIe.
- Excellent communication skills, with the ability to work across Hardware and Software teams.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 join a team with the mission to develop a modeling environment which will be used to analyze future SoC architectures with the goal of optimizing the overall performance and Total Cost of Ownership (TCO). You will help develop a comprehensive modeling environment used to evaluate the performance at the SoC level, the node level, and cluster level. You will run and analyze traces and simpoints from performance benchmarks and workloads, as well as collaborate with SoC hardware architects to provide analysis and direction on architectural proposals.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Develop simulators and architectural models of general compute SoCs.
- Collaborate with system architects, SoC and IP architects as well as software and application experts to understand the current and future SoC requirements.
- Drive architectural analysis and evaluation of future SoC design features.
- Perform pre-silicon performance simulation and correlate with post-silicon measurements.
- Communicate analysis results in both qualitative and quantitative fashion.
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