Software Engineer Manager, TPU Silicon Validation

Minimum qualifications:

• Bachelor’s degree, or equivalent practical experience.
  
• 8 years of experience in software development using C and C++.
• 3 years of experience working with embedded systems and embedded operating systems.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience with test design.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization.
  
• Experience developing robust test content for complex chips and hardware systems.
• Experience working with large, multi-die accelerators, including familiarity with key technologies such as HBM/DDR memory, PCIe or high-speed interfaces, or ARM/RISC-V architectures.
• Expertise in embedded software or ASIC firmware development using C and C++.

About the job

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 TPU Platform Enablement and Silicon Validation team develops the critical software required for chip functionality and performance validation in both pre- and post-silicon environments.

As a Software Engineering Manager, you will lead a group focused on building the software and test content necessary for validating our cutting-edge chip and hardware systems.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities

• Lead and manage the team responsible for TPU development and Silicon Validation by setting clear priorities, providing coaching and performance feedback, and aligning team strategies with broader organizational goals.
• Define the technical roadmap, guide complex system designs to solve ambiguous problems, and uphold engineering best practices through code reviews and architectural oversight.
• Oversee the development of comprehensive test frameworks, core test generators, and IP test content required to drive pre- and post-silicon ASIC validation across simulation, emulation, and silicon environments.
• Direct the creation of critical simulation and modeling tools (GRM and ISS), embedded firmware/software for test boards, and innovative tests and coverage analysis methodologies to maximize hardware stress testing.
• Collaborate seamlessly with chip, hardware, system, and software engineering teams to debug complex issues and comprehensively validate chip and system features.