Silicon AI/ML Simulation Modelling Engineer, Google Cloud

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 2 years of experience in developing simulation models for hardware IPs, or a PhD degree in lieu of industry experience
• Experience in developing software systems in modern C++.

Preferred qualifications:

• Experience in Hardware and Software co-design.
  
• Experience in applying computer architecture principles to solve open-ended problems.
• Knowledge of design of digital logic at the register-transfer level (RTL) using Verilog.
• Knowledge of processor design or accelerator designs and mapping Machine Learning (ML) models to hardware architectures.

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 diverse 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 be responsible for developing functional or performance models for Machine Learning (ML) compute IPs and integrating them with the Cloud TPU SoC model. You will be working with ML and SoC architecture teams to understand the instruction set and architecture of ML IPs in detail. You will be working with pre-silicon (e.g., DV, emulation), post-silicon, and Software teams who will be using these models as a part of their validation flow and aid in delivering quality designs for next generation data center accelerators.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

• Study the instruction set and architecture of the Machine Learning (ML) IPs and drive discussions on the delta features from the previous generation.
• Develop functional or performance models for the ML IPs. Integrate the functional models with the Cloud TPU SoC model and deliver the single source of truth architectural reference.
• Work with pre-silicon verification and post-silicon validation teams to deploy the models into their validation flows.
• Work with compiler and software teams to enable them to left-shift their development activity.