Sr. PD Methodology Engineer, Annapurna Labs - Cloud Scale Machine Learning

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

Description

Annapurna Labs (our organization within AWS Utility Computing) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. We have data center locations in the U.S., Europe, Singapore, and Japan, and customers across all industries.

Custom SoCs (System on Chip) live at the heart of AWS Machine Learning servers. As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data centers including AWS Inferentia, Trainium Systems (our custom designed machine learning inference and training datacenter servers). Our success depends on our world-class server infrastructure; we’re handling massive scale and rapid integration of emergent technologies. We’re looking for an ASIC Physical Design Methodology Engineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs.

Key job responsibilities

• Define, develop and deploy innovative physical design and verification methodologies (RTL2GDS) for ML Accelerator chips in advanced nodes
• Drive Optimizations in CAD flows/methodologies for PPA and TAT improvements
• Work with EDA tool vendors to evaluate new methods, resolve bugs, improve usability.
• Fine tune cloud infrastructure to improve compute and storage utilization for physical design work.
• Interface directly with RTL, Physical Design, Package Design, DFT teams to improve methodologies and efficiencies.
• Be able to independently troubleshoot digital tool flow usage and deploy solutions;
• Fluent in scripting languages such as TCL, Python, etc. and able to build scalable and efficient flows to support parallel design developments
• Create Dashboard and Central reports for project tracking and visualizing QoR/stats

A day in the life

Basic Qualifications

• BS + 10yrs or MS + 7yrs in EE/CS
• 5+ years developing physical design methodology or CAD flows in synthesis, PNR, and sign-off areas for advanced technology nodes.
• Proficient in programming/scripting languages (Perl, Python, C++)
• Solid understanding of ASIC physical design, and methodologies including synthesis, place and route, STA, IR, formal and physical verification.
• Demonstrated level of expertise in PD tools such as Innovus, ICC2, Fusion Compiler, STA, and Sign-Off.
• Proven track record of delivering metric driven PPA flow development and support.

Preferred Qualifications

• Expertise in high-performance, low-power physical design, and implementation techniques with industry standard synthesis, PnR, or Signoff tools.
• Excellent programming skills in languages like Python, Perl, TCL, Shell, etc. Good understanding of algorithms with emphasis on optimizing algorithms.
• Knowledge of technology nodes across foundries
• Experience in evaluating multiple vendor solutions and driving tool decisions.
• Knowledge of creating dashboards and status reports for various EDA tool outputs, QOR metrics and analyzing trends (synthesis, pnr, signoff etc)
• Experience with machine learning

• Excellent verbal and written communications
• Ability to work in dynamic work environment with changing needs and requirements
• Ability to provide mentorship, guidance to junior engineers and be a effective team player
• Meets/exceeds Amazon’s leadership principles requirements for this role
• Meets/exceeds Amazon’s functional/technical depth and complexity for this role

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Austin - 159,200.00 - 215,300.00 USD annually

Company - Annapurna Labs (U.S.) Inc.

Job ID: A2972788