PD Engineer, Annapurna Labs

Description 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

• Drive block physical implementation through synthesis, floor planning, bus / pin planning, place and route, power/clock distribution, congestion analysis, timing closure, IR drop analysis, physical verification, ECO and sign-off
• 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, 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
• Block Design using EDA tools (examples: Cadence, Mentor Graphics, Synopsys, or Others) including synthesis, equivalency verification, floor planning, bus / pin planning, place and route, power/clock distribution, congestion analysis, timing closure, IR drop analysis, physical verification, and ECO
• Deep understanding on sign-off activities (timing, ir/em, physical verification) Preferred Qualifications
• Experience in machine learning applications
• Experience with written and verbal communication and presentation
• Expertise using CAD tools (examples: Cadence, Mentor Graphics, Synopsys, or Others) develop flows for synthesis, formal verification, floor planning, bus / pin planning, place and route, power/clock distribution, congestion analysis, timing closure, IR drop analysis, physical verification, and ECO
• 4+ years of integrating IP and ability to specify and drive IP requirements in the physical domain.
• Experience in extraction of design parameters, QOR metrics, and analyzing trends
• 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. 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, TX, Austin

• 136,000.00
• 184,000.

00 USD annually