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Production Engineers at Facebook are hybrid software/systems engineers who ensure that Facebook's services run smoothly and have the capacity for future growth. They are embedded in every one of Facebook's product and infrastructure teams, and are core participants in every significant engineering effort underway in the company.

Our team is comprised of varying levels of experience and backgrounds, from new grads to industry. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We sail into uncharted waters every day at Facebook in Production Engineering, and we are always learning.

This position is full-time.
Production Engineer Responsibilities
Own back-end services like our Hadoop data warehouses, front-end services like Messenger and Newsfeed, infrastructure components like our Memcache infrastructure, and everything in between
Write and review code, develop documentation and capacity plans, and debug the hardest problems, live, on some of the largest and most complex systems in the world
Together with your engineering team, you will share an on-call rotation and be an escalation contact for service incidents
Partnered alongside the best engineers in the industry on the coolest stuff around, the code and systems you work on will be in production and used by millions of users all around the world

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As a CPU Workload Analysis Researcher within Google Cloud's MSCA organization, you will be integral to developing silicon solutions powering Google's direct-to-consumer products. You will join a Research and Development team focused on analyzing and profiling workloads requirements within the Google Cloud environment. Your role will involve conducting in-depth research on CPU optimization, feature development, and ML usages over compute platforms, contributing to identifying key areas of investment and future opportunities. This role offers a unique opportunity to perform groundbreaking research with a significant impact on both research methodologies and industry products, within the server chip architecture team. Your work will directly influence the next generation of hardware experiences for millions of Google users and Cloud customers.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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.