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Microsoft Azure Core ILDC (Microsoft Israel Development Center) team is a new and fast growing team, with multiple intriguing projects in different networking areas. Our team develops products spanning across all layers of the networking stack, from Field Programmable Gate Arrays (FPGA) offloading, through kernel drivers, Data Plane Development Kit (DPDK) applications up to user space code and more. Microsoft Azure is building the fastest and most secure networks in public cloud. ILDC (which is Microsoft Azures Israel Development Centers) is seeking candidates who ideally have networking and/or security background.


We are looking for excellent engineers who want to create, impact and collaborate with the best-in-class engineers. Be part of a growing team and contribute to its success. Innovate, solve problems and work as part of a team. Build network systems and services, taking products all the way from an idea to production. Join us as a Software Engineer to build the worlds fastest public cloud and make a difference to millions of people across the planet.

Microsofts mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities
You will develop Windows/Linux drivers, services and applications.

You will be participating in multidisciplinary projects in Microsoft, with our Hardware and OS partners.

You will collaborate with different partners in Azure Core team in Israel, US, India and Europe.

You will contribute to new feature design, implementation, testing and deployment at scale.

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 Design Verification Engineer, you will work as part of a Research and Development team building verification components, constrained-random testing, system testing, and verification closure. As part of our server chip design team, you will verify complex digital designs. You will collaborate with design and verification engineers in active projects and perform verification. You will be responsible for the full lifecycle of verification which can range from verification planning, test execution, or collecting and closing coverage.

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
Plan the verification of digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification scenarios.
Create and enhance constrained-random verification environments using SystemVerilog or formally verify designs with SystemVerilog Assertions (SVA) and industry leading formal tools.
Identify and write all types of coverage measures for stimulus and corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Apply close coverage measures to identify verification holes and to show progress towards tape-out.

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.