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Low Power Design Expert for Sustainable AI Solutions

2 weeks ago


Bangalore Metropolitan Area, India beBee Careers Full time
Job Description

We are seeking a highly skilled Low Power UPF Front-End Design Engineer to join our team. The ideal candidate will have deep expertise in low-power architecture, UPF-based power intent implementation, and front-end RTL methodologies.

About the Role

The successful candidate will define and develop low-power architectures and strategies using Unified Power Format (UPF). They will drive power intent specification, verification, and validation throughout the design lifecycle, collaborating with front-end design teams to ensure power-efficient RTL design, clock gating, power gating, voltage scaling, and retention strategies.

  • Develop and implement low-power architectures and strategies using UPF
  • Drive power intent specification, verification, and validation
  • Collaborate with front-end design teams to ensure power-efficient design
  • Work closely with verification teams to develop power-aware simulation methodologies and tools
Key Responsibilities

The successful candidate will perform power analysis, modeling, and trade-offs at the architectural and RTL level. They will guide the synthesis and timing closure process with power intent considerations and define industry best practices in low-power methodologies, tools, and flows.

  • Perform power analysis, modeling, and trade-offs
  • Guide the synthesis and timing closure process
  • Define industry best practices in low-power methodologies
Requirements

The ideal candidate will have deep expertise in low-power architecture and UPF-based power intent implementation. They will also have strong collaboration skills with system architects, RTL design engineers, and back-end teams, as well as experience with front-end RTL methodologies and power-efficient design techniques.

  • Deep expertise in low-power architecture and UPF-based power intent implementation
  • Strong collaboration skills
  • Experience with front-end RTL methodologies