RTL Design Engineer, Cloud Silicon

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

In this role, you will be part of a team developing Application-specific integrated circuit (ASICs) used to accelerate machine learning computation in data centers. You will collaborate with members of architecture, verification, power and performance, physical design to specify and deliver quality designs for next generation data center accelerators. You will solve technical problems with micro-architecture and practical reasoning solutions, and evaluate design options with complexity, performance, and power.

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.

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 4 years of experience in ASIC development with Verilog, SystemVerilog, Very High Speed Integrated Circuit (VHSIC), Hardware Description Language, or Chisel.
• Experience with micro-architecture and designing IPs and subsystems.
• Experience in ASIC design verification, synthesis, timing/power analysis, and design for testing.

Preferred qualifications:

• Experience with coding languages (e.g., Python or Perl).
• Experience in System on a Chip (SoC) designs and integration flows.
• Knowledge of arithmetic units, bus architectures, processor design, accelerators, or memory hierarchies.
• Knowledge of high performance and low power design techniques.