Google

TPU, Pre-Silicon Validation Engineer, Google Cloud

Posted On

April 22, 2025

Location

Bengaluru, Karnataka

Experience Level

Freshers/Experienced

Job Type

Permanent

Apply By

May 8, 2025

Job Description

Enable bring-up of chip features through firmware and driver stack. Integrate and validate hardware and software designs in pre-silicon.
Architect and design Application-Specific Integrated Circuit (ASIC) models for Emulation/Field Programmable Gate Array (FPGA) Prototypes. Design Register-Transfer Level (RTL) transformations to optimize mapping to Emulation/FPGA platforms and design solutions to improve Internet Protocol (IP) modeling.
Design solutions to improve hardware modeling accuracy and scale to various system configurations and enable serving of ASIC models for software and validation teams.
Bringup chip features on software reference models and hardware prototypes (e.g., Emulation/FPGA) and drive debug discussions with design/design validation/physical design/software/architecture teams and help root-cause failures.
Develop the integration plan with software and system partners, coordinate hardware and software delivery and benchmark performance.

Minimum qualifications:

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
5 years of experience in architecture, hardware, digital design, and software co-design
3 years of experience in Verilog/SystemVerilog.
Experience in computer architecture and digital design or Internet Protocol (IP) integration (e.g., Peripheral Component Interconnect Express (PCIe), Double Data Rate (DDR) memory).

Preferred qualifications:

Master's degree in Electrical Engineering, Computer Science, or a related field.
4 years of experience working on Field Programmable Gate Array (FPGA) platforms or Emulation platforms with Internet Protocols (IPs) (e.g., Peripheral Component Interconnect Express (PCIe), Double Data Rate (DDR) memory, Gigabit Ethernet, Flash).
Experience in developing architectures for Machine Learning Accelerators.
Experience in writing or debugging Verilog/Register-Transfer Level (RTL) code for ASIC/FPGA designs, waveform debug skills with knowledge of chip design flows.

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
5 years of experience in architecture, hardware, digital design, and software co-design
3 years of experience in Verilog/SystemVerilog.
Experience in computer architecture and digital design or Internet Protocol (IP) integration (e.g., Peripheral Component Interconnect Express (PCIe), Double Data Rate (DDR) memory).

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.

In this role, you will integrate hardware and software stacks and operate them on emulation platforms for pre-silicon validation of our Google Cloud Tensor Processing Unit (TPU) projects. You will create software-based custom test cases, workloads, test generators, infrastructure, analysis tools, and debugging tools. You will be responsible for silicon bring-up, validation, characterization and qualification, and sustaining programs and their quality. You will help ensure our fleet runs at maximum efficiency, and help debug and root when causing issues. You will collaborate with Product Firmware, System Software and Application-Specific Integrated Circuit (ASIC) Design in the development of tools, validation firmware, functional and performance tests, and testing infrastructure for our platforms and Google Cloud data center systems.

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 Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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