דרושים » פיתוח תוכנה » Modeling and Performance Architect, Google Cloud

Our computational challenges are so big, complex and unique we can't just purchase off-the-shelf hardware, we've got to make it ourselves. Your team designs and builds the hardware, software and networking technologies that power all of Google's services. As a Hardware Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.

In this role, you will work with internal system teams and the System-on-Chip (SoC) Architecture team to develop an understanding of the SoC, performance metrics, benchmarks/measuring tools, and available optimization knobs. You will define methods and technologies to model SoC performance at different accuracy levels by supporting architectural explorations and decision-making. In addition, you will correlate performance projections with measured post-silicon data.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

Responsibilities
Develop simulators and architectural models of general-compute SoCs.
Collaborate with system architects, SoC and IP architects/designers, and software and application experts to understand current and future requirements.
Participate in architectural and design evaluation of SoC designs.
Perform pre-silicon performance simulation and correlate with post-silicon measurements.
Communicate analysis results qualitatively and quantitatively.