Co-Design Engineer, Google Cloud TPU

Share Performance Co-Design Engineer, Google Cloud TPU

Google Sunnyvale, CA, USA

X In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
• 10 years of experience in computer architecture, chip architecture, or hardware-software co-design.
• Experience developing systems for performance modeling, simulation, or system analysis.

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
• Experience architecting hardware solutions or performance optimizations for large-scale ML training and inference.
• Experience with deep learning frameworks such as Tensor Flow or PyTorch.
• Deep understanding of ML trends, business drivers, and the software ecosystem.
• Ability to engage and collaborate with hardware designers, software architects, and ML researchers.

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.

As a Staff Co-Design Engineer on the TPU Architecture team, you will act as a key technical anchor bridging the gap between model architecture innovation and next-generation hardware design. Operating cross-functionally across AI research and engineering, you will help shape the architectural roadmap for our future machine learning serving and training capabilities. You will drive the integration of Machine Learning (ML) research such as the training and serving of massive foundation models with advanced silicon architectures to deliver industry-leading, high-performance, and power-efficient accelerators.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

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…