Senior PD Methodology Engineer for ML Accelerators - RSUs

Amazon Web Services (AWS); Austin (TX); On-site; USD 159,200 - 215,300; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Annapurna Labs (U.S.) Inc. in Austin, TX, is seeking an ASIC Physical Design Methodology Engineer to lead design and verification innovation for ML accelerator chips. You will drive PPA improvements and collaborate across RTL, PD, and DFT teams to deliver scalable, high-quality flows.

The role requires strong scripting in TCL, Python, Perl, and C++, plus hands-on use of PD tools like Innovus, ICC2, and Fusion Compiler. This position offers competitive compensation and benefits.

Qualifications

• BS or MS in EE/CS with relevant years of experience in physical design.
• 5+ years developing physical design methodology or CAD flows for advanced nodes.
• Proficient in programming/scripting languages (Perl, Python, C++).
• Solid understanding of ASIC physical design and PD tools.

Responsibilities

• Define, develop and deploy innovative physical design and verification methodologies for ML accelerator chips.
• Drive optimizations in CAD flows/methodologies for PPA and TAT improvements.
• Work with EDA tool vendors to evaluate new methods and resolve issues.
• Fine tune cloud infrastructure to improve compute and storage utilization for physical design.
• Interface with RTL, Physical Design, Package Design, DFT teams to improve methodologies.

Skills

ASIC physical design

CAD flows

Python

Perl

C++

Scripting

PPA flow

Place and route

STA

Formal verification

Digital tool flow

Dashboards

Education

BS in EE/CS

MS in EE/CS

Tools

Innovus

ICC2

Fusion Compiler

STA

Sign-Off

Job description

Annapurna Labs (U.S.) Inc. in Austin, TX, is seeking an ASIC Physical Design Methodology Engineer to lead design and verification innovation for ML accelerator chips. You will drive PPA improvements and collaborate across RTL, PD, and DFT teams to deliver scalable, high-quality flows.

The role requires strong scripting in TCL, Python, Perl, and C++, plus hands-on use of PD tools like Innovus, ICC2, and Fusion Compiler. This position offers competitive compensation and benefits.