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Posted via Amazon Jobs

PD Methodology Engineer II, Annapurna Labs

Posted Aug 3, 2026

Role at a glance

Salary
$157.3K – $212.8K/yr
Location
Cupertino, California, United States Austin, Texas, United States
Work arrangement
On-site
Employment
Full-time
Experience
Minimum of 3+ years in developing design methodology or CAD flows in synthesis, PNR, or sign-off areas for advanced technology nodes
Education
Bachelor's degree in Electrical Engineering or a related field

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Role Summary

AI-generated

The Cloud-Scale Machine Learning Acceleration team designs and optimizes hardware for data centers, including AWS Inferentia machine learning inference products. The role provides leadership in applying new technologies to large-scale deployments and improving product performance, quality, and cost.

What You'll Do

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

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Required

  • Bachelor's degree in Electrical Engineering or a related field
  • Minimum of 3+ years in developing design methodology or CAD flows in synthesis, PNR, or sign-off areas for advanced technology nodes
  • Experience in writing production scripts for implementation and sign-of. tools in TCL, Perl, and/or Python
  • Solid understanding of ASIC physical design, physical design flows, and methodologies including synthesis, place and route, STA, formal verification
  • Proven track record of delivering metric driven PPA flow development and support

Preferred

  • Experience in machine learning applications
  • Knowledge of programming languages such as C/C++, Python, Java or Perl
  • Demonstrated level of expertise in PD tools such as Innovus, ICC2, FusionCompiler, STA, and Sign-Off
  • Experience in evaluating multiple vendor solutions and driving tool decisions
  • Experience in high-performance, low-power physical design, and implementation techniques with industry standard synthesis, PnR, or Signoff tools
  • Excellent verbal and written communications

Original job description

Content provided by the employer

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 technologies such as AWS Inferentia which is a machine learning inference product designed to deliver high performance at low cost.

You’ll provide leadership in the application of new technologies to large scale deployments in a continuous effort to deliver a world-class customer experience. This is a fast-paced, intellectually challenging position, and you’ll work with thought-leaders in multiple technology areas. You’ll have relentlessly high standards for yourself and everyone you work with, and you’ll be constantly looking for ways to improve our products' performance, quality and cost. We’re changing an industry, and we want individuals who are ready for this challenge and want to reach beyond what is possible today.

Key job responsibilities
- You will create and support innovative physical design methodology and CAD flows.
- Develop cloud infrastructure to support physical design work.
- Drive improvement in RTL2GDS flows/methodology for PPA and TAT improvement.
- Create Dashboard/central reports for project tracking and visualizing QoR/stats
- Interface directly with RTL, Physical Design, Package Design, DFT and other teams to improve methodologies and efficiencies and drive efforts to resolution.
- Work with EDA tool vendors to evaluate new tools, solve bugs, improve usability, etc.

Basic Qualifications

- Bachelor's degree in Electrical Engineering or a related field
- Minimum of 3+ years in developing design methodology or CAD flows in synthesis, PNR, or sign-off areas for advanced technology nodes
- Experience in writing production scripts for implementation and sign-of. tools in TCL, Perl, and/or Python
- Solid understanding of ASIC physical design, physical design flows, and methodologies including synthesis, place and route, STA, formal verification
- Proven track record of delivering metric driven PPA flow development and support

Preferred Qualifications

- Experience in machine learning applications
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Demonstrated level of expertise in PD tools such as Innovus, ICC2, FusionCompiler, STA, and Sign-Off
- Experience in evaluating multiple vendor solutions and driving tool decisions
- Experience in high-performance, low-power physical design, and implementation techniques with industry standard synthesis, PnR, or Signoff tools
- Excellent verbal and written communications

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, CA, Cupertino - 157,300.00 - 212,800.00 USD annually
USA, TX, Austin - 136,000.00 - 184,000.00 USD annually
amazon

About the company

amazon

Large Enterprise

Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.