Cloud-Scale PD Engineer II: PPA, RTL2GDS & CAD Flows

Socket.dev; Austin (TX); On-site; USD 136,000 - 184,000; Full time

Job summary

Amazon's Cloud-Scale Machine Learning Acceleration team designs and optimizes hardware in data centers, including ASIC physical design, RTL2GDS flows, and PPA enhancements for high performance at scale.

You will develop CAD methodologies, build cloud infrastructure for design work, and collaborate with RTL, Physical Design, and EDA vendors to deliver metrics-driven improvements in cost and performance.

Qualifications

• Bachelor’s degree in Electrical Engineering or related field.
• 3+ years designing CAD flows for synthesis, PNR, or sign-off in advanced nodes.
• Experience scripting production tools in TCL/Perl/Python.
• Strong understanding of ASIC physical design and flows (synthesis, place & route, STA, formal verification).
• Track record delivering metric-driven PPA flow development.

Responsibilities

• Create and support innovative physical design methodology and CAD flows.
• Develop cloud infrastructure to support physical design work.
• Drive improvements in RTL2GDS flows/methodology for PPA and TAT improvement.
• Create dashboards and central reports for project tracking and visualizing QoR/stats.
• Interface with RTL, Physical Design, Package Design, DFT and other teams to improve methodologies and efficiencies.
• Work with EDA tool vendors to evaluate new tools, solve bugs, improve usability.

Skills

Scripting (TCL/Perl/Python)

ASIC physical design knowledge

PPA flow development

Education

Bachelor's degree in Electrical Engineering or related field

Tools

Innovus

ICC2

FusionCompiler

STA

Sign-Off tools

Job description

Amazon's Cloud-Scale Machine Learning Acceleration team designs and optimizes hardware in data centers, including ASIC physical design, RTL2GDS flows, and PPA enhancements for high performance at scale.

You will develop CAD methodologies, build cloud infrastructure for design work, and collaborate with RTL, Physical Design, and EDA vendors to deliver metrics-driven improvements in cost and performance.