Amazon
Sr. Static Timing Technical Lead, Hardware Compute Group
Amazon, Sunnyvale, California, United States, 94087
Sr. Static Timing Technical Lead, Hardware Compute Group
Job ID: 2857062 | Amazon.com Services LLC The team that built the innovative Silicon IP AZ1 Neural Edge that is powering the latest generation of Echo devices is looking for a Sr. SOC Physical Design Engineer to continue to innovate on behalf of our customers. We are a part of Amazon Lab126 that revolutionized reading with our Kindle family of products and reimagined user experience through Echo and Alexa. We want you to help us build on the success of our first generation of ML accelerator at edge.
Work hard. Have fun. Make history. Roles & Responsibilities:
Includes definition and development of signoff methodology and corresponding implementation solution. Flow for STA, Crosstalk Delay and Crosstalk Noise analysis for digital ASIC/SoCs. Full chip timing constraints development, full chip / Sub-System STA and Signoff for a complex, multi-clock, multi-voltage SoC. Streamlining the timing signoff criterions, timing analysis methodologies and flows. Analyze and incorporate advance timing signoff flows (AOCV, POCV Based STA, IR Drop aware STA) into SoC timing signoff flow. Work for Systems and Architecture, SoC Integration, Verification, DFT, Mixed Signal, IP owners, Synthesis, Place & Route and other local/remote teams to address the design challenges in the context of timing sign-off. Concepts of CRPR, clock paths analysis and tweaks to meet timing. Multi Corner and Multimode analysis. Close timing at Signoff corners covering the entire modes, delay corners for cells and interconnects. BASIC QUALIFICATIONS
Bachelor’s degree or higher in EE, CE, or CS. 10+ years or more of practical semiconductor implementation experience. Scripting experience with Perl, Python, tcl, shell and drive to automate flows. Proficiency in chip front-end and back-end implementation tools such as Fusion compiler, Design Compiler, ICC2 or Innovus and Primetime, Tempus. Must have good communication and analytical skills. Should be able to work closely with IP Design teams and Backend Physical Design teams across multiple sites. PREFERRED QUALIFICATIONS
PhD in Computer Science, Electrical Engineering, or related field. Experience with memory compiler. Experience with formal equivalence – Cadence Conformal/Synopsys Formality. Have in-depth knowledge of entire design process from Design specification, defining architecture, micro-architecture, RTL design and functional verification. Experience with DFT and DFM flows. 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. 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
this link
for more information.
#J-18808-Ljbffr
Job ID: 2857062 | Amazon.com Services LLC The team that built the innovative Silicon IP AZ1 Neural Edge that is powering the latest generation of Echo devices is looking for a Sr. SOC Physical Design Engineer to continue to innovate on behalf of our customers. We are a part of Amazon Lab126 that revolutionized reading with our Kindle family of products and reimagined user experience through Echo and Alexa. We want you to help us build on the success of our first generation of ML accelerator at edge.
Work hard. Have fun. Make history. Roles & Responsibilities:
Includes definition and development of signoff methodology and corresponding implementation solution. Flow for STA, Crosstalk Delay and Crosstalk Noise analysis for digital ASIC/SoCs. Full chip timing constraints development, full chip / Sub-System STA and Signoff for a complex, multi-clock, multi-voltage SoC. Streamlining the timing signoff criterions, timing analysis methodologies and flows. Analyze and incorporate advance timing signoff flows (AOCV, POCV Based STA, IR Drop aware STA) into SoC timing signoff flow. Work for Systems and Architecture, SoC Integration, Verification, DFT, Mixed Signal, IP owners, Synthesis, Place & Route and other local/remote teams to address the design challenges in the context of timing sign-off. Concepts of CRPR, clock paths analysis and tweaks to meet timing. Multi Corner and Multimode analysis. Close timing at Signoff corners covering the entire modes, delay corners for cells and interconnects. BASIC QUALIFICATIONS
Bachelor’s degree or higher in EE, CE, or CS. 10+ years or more of practical semiconductor implementation experience. Scripting experience with Perl, Python, tcl, shell and drive to automate flows. Proficiency in chip front-end and back-end implementation tools such as Fusion compiler, Design Compiler, ICC2 or Innovus and Primetime, Tempus. Must have good communication and analytical skills. Should be able to work closely with IP Design teams and Backend Physical Design teams across multiple sites. PREFERRED QUALIFICATIONS
PhD in Computer Science, Electrical Engineering, or related field. Experience with memory compiler. Experience with formal equivalence – Cadence Conformal/Synopsys Formality. Have in-depth knowledge of entire design process from Design specification, defining architecture, micro-architecture, RTL design and functional verification. Experience with DFT and DFM flows. 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. 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
this link
for more information.
#J-18808-Ljbffr