PD Methodology Engineer II, Annapurna Labs

About the role

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—a machine learning inference product designed to deliver high performance at low cost. You’ll provide leadership in applying new technologies to large-scale deployments, continuously improving a world-class customer experience. This is a fast-paced, intellectually challenging position where you’ll collaborate with thought leaders across multiple technology areas. You’ll uphold relentlessly high standards for yourself and your team, constantly seeking ways to enhance product performance, quality, and cost. We’re transforming an industry, and we seek individuals ready to embrace this challenge and push beyond today’s possibilities.

Responsibilities

• 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 (Power, Performance, Area) and TAT (Turnaround Time) enhancement.
• Create dashboards and central reports for project tracking and visualizing QoR (Quality of Results) and statistics.
• Interface directly with RTL, Physical Design, Package Design, DFT, and other teams to improve methodologies, efficiencies, and resolve issues.
• Work with EDA tool vendors to evaluate new tools, resolve bugs, and improve usability.

Requirements

• Bachelor's degree in Electrical Engineering or a related field.
• Minimum of 3+ years of experience developing design methodology or CAD flows in synthesis, PNR (Place and Route), or sign-off areas for advanced technology nodes.
• Experience writing production scripts for implementation and sign-off tools in TCL, Perl, and/or Python.
• Solid understanding of ASIC physical design, physical design flows, and methodologies, including synthesis, place and route, STA (Static Timing Analysis), and 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 expertise in PD (Physical Design) tools such as Innovus, ICC2, FusionCompiler, STA, and Sign-Off.
• Experience evaluating multiple vendor solutions and driving tool decisions.
• Experience in high-performance, low-power physical design and implementation techniques using industry-standard synthesis, PnR, or Signoff tools.
• Excellent verbal and written communication skills.

Benefits

Amazon offers comprehensive benefits, including:

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with options for supplemental life plans).
• Employee Assistance Program (EAP) and mental health support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and surrogacy reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.

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

Pay

• USA, CA, Cupertino: $157,300.00 - $212,800.00 USD annually.
• USA, TX, Austin: $136,000.00 - $184,000.00 USD annually.

Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location.