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Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

The Sources Infrastructure team plays a key role in GCP's database migration and data streaming strategy. Our goal is to enable customers to seamlessly move and replicate data from any source into Google Cloud by building and enhancing the source offerings for Datastream and the Database Migration Service (DMS).

In this role, you will develop and maintain the data ingestion part of the platform, the part that connects to external sources and extracts the data.

Google Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Googles 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.

Responsibilities
Set and communicate team priorities that support the organization's goals. Align strategy, processes, and decision-making across teams.
Develop the mid-term technical goal and roadmap within the scope of the multiple team(s). Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
Provide technical leadership on sources projects, involving participating in sessions, creating design documents, and conducting code reviews.
Manage, develop, and mentor a team of skilled engineers, fostering a culture of collaboration and innovation and facilitating their career growth.

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.
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
Build C/C++ firmware running on embedded processors with limited memory footprints on the SoCs.
Develop tools to update and debug the firmware, enable emulation, chip bringup, and hardware debugging.
Play key roles in emulation, chip bring up, and SoC deployment, and contribute to all layers of the data center software stack to deploy SoCs to production.
Create code generators to generate C++ code based on hardware specifications.

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, and you will build verification components, constrained-random testing, system testing, and verification closure. As part of our server chip design team, you will verify digital designs. You will collaborate closely with design and verification engineers in projects and perform direct verification. You'll build efficient and effective constrained-random verification environments that exercise designs through their corner-cases and expose all types of bugs. You will manage the full lifecycle of verification which can range from verification planning, test execution or collecting, and closing coverage.

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 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/UVM, or Specman.
Identify and write all types of coverage measures for stimulus and corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Lead coverage measures to identify verification holes and to show progress towards tape-out.