In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven 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.
Minimum qualifications:
- 8 years of experience leading an embedded or firmware development team.
- Experience with embedded software or firmware development in C/C++.
- Experience with bringing up bare-metal environments on SoCs.
- Experience in leading firmware debugs on silicon and usage of debug tools such as TRACE32, OpenOCD, etc.
Preferred qualifications:
- Experience with ARM and RISC-V architectures.
- Experience in using emulation platforms for firmware enablement, validation, and debug.
- Experience in industry standard software development practices and agile methodologies.
- Understanding of SoC architecture and interfaces (e.g., AXI, DDR, PCIe, etc.).