Physical Design Methodology Engineer, Annapurna Labs

Amazon; Cupertino (CA); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is on the lookout for a talented Physical Design Methodology Engineer to join their innovative team. In this role, you will design and optimize hardware for cutting-edge cloud server platforms, working with advanced technologies and thought leaders in the field. This is a fast-paced position that requires high standards and a commitment to continuous improvement. If you're ready to tackle complex challenges and make a significant impact in the tech industry, this opportunity is perfect for you. Join a diverse and inclusive workplace where your contributions will help shape the future of cloud infrastructure.

Qualifications

• 3+ years in developing design methodology or CAD flows.
• Experience in writing production scripts in TCL, Perl, or Python.
• Solid understanding of ASIC physical design and methodologies.

Responsibilities

• Create and support innovative physical design methodology and CAD flows.
• Develop cloud infrastructure to support physical design work.
• Interface with multiple teams to improve methodologies and efficiencies.

Skills

Physical Design Methodology

CAD Flows

Python Programming

TCL Scripting

Perl Scripting

ASIC Physical Design

Machine Learning

Communication Skills

Education

Bachelor's Degree in Electrical Engineering

Master's Degree in Electrical Engineering

Bachelor's Degree in Computer Engineering

Master's Degree in Computer Science

Tools

Innovus

ICC2

FusionCompiler

STA Tools

Job description

Physical Design Methodology Engineer, Annapurna Labs

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. AWS has the broadest and deepest set of machine learning and AI services for our customers’ businesses. We are seeking experienced Physical Design Engineer to build the next generation of our cloud server platforms. Our success depends on our world-class infrastructure; we’re handling massive scale and rapid integration of emergent technologies.

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 Responsibilities

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

Minimum Requirements

1. Bachelors or Master’s degree in EE, CE, or CS.
2. Minimum of 3+ years in developing design methodology or CAD flows in synthesis, PNR, or sign-off areas for advanced technology nodes.
3. Experience in writing production scripts for implementation and sign-off tools in TCL, Perl, and/or Python.
4. Solid understanding of ASIC physical design, physical design flows, and methodologies including synthesis, place and route, STA, formal verification.
5. Proven track record of delivering metric driven PPA flow development and support.
6. Demonstrated level of expertise in PD tools such as Innovus, ICC2, FusionCompiler, STA, and Sign-Off.
7. Experience in evaluating multiple vendor solutions and driving tool decisions.
8. Experience in high-performance, low-power physical design, and implementation techniques with industry standard synthesis, PnR, or Signoff tools.
9. Excellent programming skills in languages like Python, Perl, TCL, Shell, etc. Good understanding of algorithms with emphasis on optimizing algorithms.
10. Experience with machine learning.
11. Excellent verbal and written communications.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.